U.S. patent application number 15/963994 was filed with the patent office on 2019-03-07 for method and system for managing lifestyle and health interventions.
The applicant listed for this patent is BETTER THERAPEUTICS LLC. Invention is credited to Kevin APPELBAUM, Mark BERMAN, Andres CAMACHO, Sourav DEY.
Application Number | 20190074080 15/963994 |
Document ID | / |
Family ID | 62148537 |
Filed Date | 2019-03-07 |
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United States Patent
Application |
20190074080 |
Kind Code |
A1 |
APPELBAUM; Kevin ; et
al. |
March 7, 2019 |
METHOD AND SYSTEM FOR MANAGING LIFESTYLE AND HEALTH
INTERVENTIONS
Abstract
Provided herein are methods and systems for managing lifestyle
and health interventions. The methods and systems described herein
can improve health outcomes for a variety of lifestyle intervention
regimens. Described herein are methods and systems for providing an
interface for a human subject, collecting subject-specific data
entered by the human subject, and comparing the subject-specific
data to a database of entry activity by prior subjects. The methods
and systems can further provide the subject with milestone
achievement input derived from the entry activity of the subject
that predicts the likelihood of success in achieving a desired
outcome. The methods and systems described herein can be used for
addressing a variety of lifestyle-related health conditions
including without limitation body weight and cardiometabolic
disorders such as type-II diabetes.
Inventors: |
APPELBAUM; Kevin; (Corte
Madera, CA) ; BERMAN; Mark; (San Francisco, CA)
; CAMACHO; Andres; (Lafayette, CA) ; DEY;
Sourav; (South San Francisco, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
BETTER THERAPEUTICS LLC |
San Francisco |
CA |
US |
|
|
Family ID: |
62148537 |
Appl. No.: |
15/963994 |
Filed: |
April 26, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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62492065 |
Apr 28, 2017 |
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62628842 |
Feb 9, 2018 |
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62629644 |
Feb 12, 2018 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04L 51/02 20130101;
H04L 67/12 20130101; G16H 20/70 20180101; G16H 20/60 20180101; G16H
50/30 20180101; G16H 10/20 20180101; G16H 10/60 20180101; G16H
50/20 20180101; G16H 20/30 20180101; G16H 15/00 20180101; G16H
80/00 20180101 |
International
Class: |
G16H 20/60 20060101
G16H020/60; G16H 20/30 20060101 G16H020/30; G16H 80/00 20060101
G16H080/00; G16H 10/60 20060101 G16H010/60; G16H 15/00 20060101
G16H015/00; G16H 50/20 20060101 G16H050/20 |
Claims
1. A method for improving a lifestyle-related health condition of a
subject, said method comprising: a. providing to said subject a
digital interface for: i. receiving a lifestyle intervention
regimen to achieve a lifestyle-related health condition milestone;
ii. entering subject-specific data for one or more validated
compliance parameters associated with said lifestyle-related health
condition milestone; and iii. optionally collecting body metric
measurements; and b. receiving from said subject and via the
digital interface, said subject-specific data for one or more
validated compliance parameters associated with said
lifestyle-related health condition milestone; c. comparing entry
activity comprised of a rate and/or number of said subject-specific
data received from said subject via the digital interface with a
database of entry activity by prior subjects; and d. providing said
subject with milestone achievement input, wherein said milestone
achievement input is derived, at least in part, from the entry
activity comprised of the rate and/or number of subject-specific
data received from said subject via said digital interface, and
predicts the subject's likelihood of success in achieving the
lifestyle-related health condition milestone at a future date.
2. A method for treating a subject having or at risk of having a
cardiometabolic disorder, said method comprising: a. providing to
said subject a digital interface for: i. receiving a lifestyle
intervention regimen to achieve a therapeutic milestone for said
cardiometabolic disorder; ii. entering subject-specific data for
one or more validated compliance parameters associated with said
therapeutic milestone for said cardiometabolic disorder; and iii.
optionally collecting body metric measurements; and b. receiving
from said subject and via the digital interface, said
subject-specific data for one or more validated compliance
parameters associated with said therapeutic milestone; c. comparing
entry activity comprised of a rate or number of said
subject-specific data received from said subject via the digital
interface with a database of entry activity by prior subjects; and
d. providing said subject with milestone achievement input, wherein
said milestone achievement input is derived, at least in part, from
the entry activity comprised of the rate and/or number of
subject-specific data received from said subject via said digital
interface, and predicts the subject's likelihood of success in
achieving the therapeutic milestone for said cardiometabolic
disorder at a future date.
3. The method according to claim 1 or 2, wherein said lifestyle
intervention regimen is selected from the group consisting of a
dietary regimen and an activity regimen.
4. The method according to claim 3, wherein said lifestyle
intervention regimen comprises a dietary regimen, and said dietary
regimen comprises a plant based diet.
5. The method of claim 4, wherein said dietary regimen further
comprises vegetables, fruit, legumes, nuts and seeds, and whole
grains.
6. The method according to claim 4, wherein said plant-based diet
comprises recipes, ingredients and local ingredient acquisition
locations.
7. The method according to claim 3, wherein said validated
compliance parameters comprise compliance parameters selected from
the group consisting of: a. generate meal plan; b. follow meal
plan; c. procure ingredients from a shopping list; d. engage with
digital interface; e. log daily targets f. log hydration; and g.
communicate with coach.
8. The method according to claim 7, wherein said validated
compliance parameters comprise at least 2, 3, 4, 5, or 6 of the
compliance parameters selected from the group consisting of: a.
generate meal plan; b. follow meal plan; c. procure ingredients
from a shopping list; d. engage with digital interface; e. log
daily targets f. log hydration; and g. communicate with coach.
9. The method according to claim 1 or 2, wherein said lifestyle
intervention comprises the activity regimen, and said daily
activity regimen comprises a type, intensity and frequency of
exercise, a daily caloric burn target, or a combination
thereof.
10. The method according to claim 9, wherein said lifestyle
intervention further comprises the dietary regimen.
11. The method according to claim 1 or 2, wherein said method
comprises collecting body weight metric measurements of said
subject via the digital interface and said milestone achievement
input is further derived from the body metric measurements of said
subject collected via the digital interface.
12. The method according to claim 1 or 2, wherein said
lifestyle-related health condition milestone or therapeutic
milestone for said cardiometabolic disorder comprises weight
loss.
13. The method according to claim 2, wherein said cardiometabolic
disorder is diabetes, and said therapeutic milestone comprises
maintenance of HbA1c, fasting glucose, fasting insulin, alanine
transaminase, and/or fasting lipids at a level indicative of
therapeutic benefit for a subject having or at risk of having
type-II diabetes.
14. The method according to claim 13, wherein the method comprises
achieving said therapeutic milestone without pharmaceutical
intervention, or with a reduced dosing of one or more
pharmaceutical interventions.
15. (canceled)
16. The method according to claim 2, wherein said cardiometabolic
disorder is heart disease, and said therapeutic milestone is
selected from the group consisting of: a. weight loss; b. improved
lipid profile; c. lower blood pressure; and d. lower resting pulse
rate.
17. The method according to claim 16, wherein the method comprises
achieving said therapeutic milestone without pharmaceutical
intervention, or with a reduced dosing of one or more
pharmaceutical interventions.
18. The method according to claim 17, wherein said pharmaceutical
intervention(s) comprise one or more interventions selected from
the group consisting of: a beta-blocking agent, an alpha-blocking
agent, an angiotensin-converting enzyme inhibitor, a statin, a
diuretic, and a calcium channel blocker.
19. The method according to claim 2, wherein said cardiometabolic
disorder is hypertension and said therapeutic milestone comprises
maintenance of a diastolic and/or systolic blood pressure at a
level indicative of therapeutic benefit for a subject having or at
risk of having hypertension.
20. The method according to claim 19, wherein the method comprises
achieving said therapeutic milestone without pharmaceutical
intervention, or with a reduced dosing of one or more
pharmaceutical interventions.
21. The method according to claim 20, wherein said pharmaceutical
intervention(s) comprise one or more interventions selected from
the group consisting of: a beta-blocking agent, an alpha-blocking
agent, an angiotensin-converting enzyme inhibitor, an angiotensin
II receptor blocker, a calcium channel blocker, a diuretic, and a
renin inhibitor.
22. The method according to claim 2, wherein said cardiometabolic
disorder is hyperlipidemia and said therapeutic milestone is
improved lipid profile.
23. The method according to claim 22, wherein the method comprises
achieving said therapeutic milestone without pharmaceutical
intervention, or with a reduced dosing of one or more
pharmaceutical interventions.
24. (canceled)
25. The method according to claim 2, wherein said cardiometabolic
disorder is coronary artery disease and said therapeutic milestone
is selected from the group consisting of: a. weight loss; b.
improved lipid profile; c. lower blood pressure; d. increased
stamina; e. reduced angina; f. reduced fluid retention; g.
increased coronary arterial blood flow; and h. reduced arterial
plaque.
26. The method according claim 25, wherein the method comprises
achieving said therapeutic milestone without pharmaceutical
intervention, or with a reduced dosing of one or more
pharmaceutical interventions.
27. The method according to claim 26, wherein said pharmaceutical
intervention(s) comprise one or more interventions selected from
the group consisting of: a. a cholesterol-modifying medication
selected from the group consisting of a statin, exetimibe, and
PCSK9 inhibitors; b. an anti-coagulant, preferably selected from
the group consisting of an anti-platelet agent (e.g. aspirin or
Plavix), warfarin, low-molecular weight heparin, a direct thrombin
inhibitor, and a factor Xa inhibitor; c. a beta-blocking agent, d.
a vasodilator; e. a diuretic; and f. an angiotensin-converting
enzyme inhibitor and an angiotensin II receptor blocking agent.
28. The method according to any claim 1 or 2, wherein said
milestone achievement input is provided by a reference
physician.
29. The method according to claim 1 or 2, further comprising: step
e) initiating direct personal feedback to said subject or
increasing the level of direct personal feedback provided to said
subject when said subject is predicted to be likely to miss their
milestone.
30. The method according to claim 1 or 2, wherein said providing to
said subject the digital interface comprises transmitting the
digital interface from a digital interface server to a user local
display.
31. The method of claim 30, wherein said user local display is a
component of a user local device, wherein said user local device
comprises the user-local display, a user local processor, and a
user local datalink.
32. The method according to claim 31, wherein said receiving from
said subject said subject-specific data comprises receiving one or
more transmissions comprising said subject-specific data: a. from
said user local datalink; and b. to a comparison engine.
33. The method according to claim 1 or 2, wherein said providing
said subject with milestone achievement input comprises
transmitting computer readable instructions to said user-local
device through said user-local datalink, wherein said computer
readable instructions are configured to display a message
comprising said input on said user-local display.
34. The method according to claim 33, wherein said message
comprises a pre-configured communication indicating likelihood of
success.
35. The method of claim 34, wherein said message further comprises
a pre-configured communication indicating an additional lifestyle
intervention for increasing likelihood of success.
36. The method of claim 35, wherein said communication indicating
an additional lifestyle intervention for increasing likelihood of
success is a message indicating an amount of increase in one or
more validated compliance parameters to achieve a predicted
likelihood of success.
37. The method of claim 35, wherein said communication indicating
an additional lifestyle intervention for increasing likelihood of
success comprises an invitation to one-on-one or small-group
coaching with a nurse practitioner, clinician, chef-educator,
behavioral psychologist, or a combination thereof.
38. The method according to claim 33, wherein said message
comprises a pre-configured communication requesting entry of
subject-specific data via the digital interface.
39. The method according to claim 33, wherein said message
comprises an interface with an automated chat module.
40. A system for performing a method according to claim 1 or 2.
41. A computer readable medium for performing a method according to
claim 1 or 2.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. 62/492,065,
entitled "METHOD AND SYSTEM FOR MANAGING LIFESTYLE AND HEALTH
INTERVENTIONS," filed Apr. 28, 2017; and U.S. 62/628,842, entitled
"SYSTEMS, METHODS, AND APPARATUSES FOR MANAGING DATA FOR ARTIFICIAL
INTELLIGENCE SOFTWARE AND MOBILE APPLICATIONS IN DIGITAL HEALTH
THERAPEUTICS," filed Feb. 9, 2018; and U.S. 62/629,644, entitled
"METHOD AND SYSTEM FOR MANAGING LIFESTYLE AND HEALTH
INTERVENTIONS," filed Feb. 12, 2018, each of which are incorporated
herein by reference in their entirety.
BACKGROUND OF THE INVENTION
[0002] Despite the long-standing, massive effort to develop
effective methods for increasing healthy behavior in human
subjects, the number of people worldwide who suffer from adverse
cardiometabolic conditions such as obesity, cardiovascular disease,
and metabolic disorders (e.g., type-II diabetes) is rapidly
growing. These conditions result in numerous medical complications,
a lowered quality of life, shortened lifespan, lost work
productivity, a strain on medical systems, and a burden on medical
insurance providers, all of which translates into increased costs
for both individuals and society.
[0003] Indeed, type 2 diabetes prevalence is at pandemic levels and
continues to rise in the U.S. and globally. NCD Risk Factor
Collaboration, The Lancet 387:1513-1530 (2016); Shi & Hu, The
Lancet 383:1947-1948 (2014). Medication costs are rising in
parallel and threaten to bankrupt national health systems. National
Diabetes Statistics Report 2017: Centers for Disease Control and
Prevention, U.S. Department of Health and Human Services
(internet); Economic Costs of Diabetes in the U.S. in 2012,
Diabetes Care 36(4):1033-1046 (2013). Despite increased use of
medications and the advent of new pharmacological interventions,
glycemic control among those with diabetes has not been improving
since 2010. Barnard et al., Change in Testing, Awareness of
Hemoglobin A1c Result, and Glycemic Control in US Adults, 2007-2014
JAMA 318(8):1825-1827 (2017).
[0004] As but one example, metformin is an antihyperglycemic agent
that can improve glucose tolerance in patients with type II
diabetes by lowering both basal and post-prandial plasma glucose.
In patients with known or suspected impaired renal function such as
those with advanced age, however, metformin administration requires
close dose monitoring and titration to prevent lactic acidosis, a
potentially fatal metabolic complication. Patients with concomitant
cardiovascular or liver disease, sepsis, and hypoxia also have an
increased risk of lactic acidosis. Thus, metformin remains an
unavailable and/or risky treatment for certain patient groups due
to its side effects.
[0005] Similarly, the pharmaceutical and surgical interventions
currently available for treatment of obesity are also associated
with significant risks and costs. Until recently, obesity
treatments included two FDA-approved drugs. Orlistat (Xenical.RTM.)
reduces intestinal fat absorption by inhibiting pancreatic lipase,
while sibutramine (Meridia.RTM.) decreases appetite by inhibiting
deactivation of the neurotransmitters norepinephrine, serotonin,
and dopamine, but sibutramine has now been taken off the market in
the U.S. and Europe. Undesirable side-effects, including effects on
blood pressure, have been reported with both these drugs. (See,
e.g., "Prescription Medications for the Treatment of Obesity," NIH
Publication No. 07-4191, December 2007). Moreover, surgical
treatments, including gastric bypass surgery and gastric banding,
are available, but only in extreme cases. These procedures can be
dangerous, and furthermore may not be appropriate options for
patients with more modest weight loss goals.
[0006] As yet another example, cardiac disease intervention can
include statins, diuretics, ACE inhibitors, calcium channel
blockers, beta blockers, alpha blockers, angioplasty, and cardiac
bypass surgery. Each of these medical or surgical interventions for
addressing cardiometabolic conditions are associated with
significant risks and costs.
[0007] More recently, efforts have been made to intervene with
individuals via a digital interface, both to collect personal
biometric data from participants and to encourage their
participation in established diabetes protocols, e.g., via group
therapy. See, e.g., US 2013/0117040 and US 2007/0072156.
Unfortunately, however, the predictive analytics employed in these
platforms are generally inadequate, placing primary reliance on
body metric data collection and comparative analysis against
generalized body metric objectives. Moreover, subsequent
interventions lack personalization and are largely historical in
focus, i.e. a determination of how far the participant has
progressed towards a given objective. Not surprisingly, then,
compliance rates for existing digital programs directed toward
behavioral changes that are targeted toward improving one or more
lifestyle-related health conditions are extremely low and generally
not durable over time. Thus, there remains a need for development
of methods and systems for managing lifestyle interventions in a
manner that provides improved compliance, improved outcomes, and/or
long-term durability of improved health.
SUMMARY OF THE INVENTION
[0008] The present invention successfully resolves this
longstanding need in the art by way of a novel, skill-focused
digital therapeutic intervention directed to modifying a patient's
lifestyle, e.g. their dietary and activity patterns, and improving
their culinary and fitness literacy, comprising a digital interface
collecting and delivering data and information to the patient and
coordinating human support. As demonstrated herein for the first
time, the subject intervention can provide a measurable improvement
in one or more therapeutic milestones in cardiometabolic disorders
such as diabetes or hypertension, increase adherence to a lifestyle
regimen, and can in some instances lead to an actual reduction in
pharmaceutical reliance.
[0009] In one aspect, the present invention provides a method for
improving a lifestyle-related health condition of a subject, said
method comprising: a) providing to said subject a digital interface
for: i) receiving a lifestyle intervention regimen to achieve a
lifestyle-related health condition milestone; ii) entering
subject-specific data for one or more validated compliance
parameters associated with said lifestyle-related health condition
milestone; and iii) optionally collecting body metric measurements;
b) receiving from said subject and via the digital interface, said
subject-specific data for one or more validated compliance
parameters associated with said lifestyle-related health condition
milestone; c) comparing entry activity comprised of a rate and/or
number of said subject-specific data received from said subject via
the digital interface with a database of entry activity by prior
subjects; and d) providing said subject with milestone achievement
input, wherein said milestone achievement input is derived at least
in part, or entirely, from the entry activity (e.g., rate and/or
number of subject-specific data entry) received from said subject
via said digital interface, and predicts the subject's likelihood
of success in achieving the lifestyle-related health condition
milestone at a future date.
[0010] In another aspect, the present invention provides a method
for treating a subject having or at risk of having a
cardiometabolic disorder, said method comprising: a) providing to
said subject a digital interface for: i) receiving a lifestyle
intervention regimen to achieve a therapeutic milestone for said
cardiometabolic disorder; ii) entering subject-specific data for
one or more validated compliance parameters associated with said
therapeutic milestone for said cardiometabolic disorder; and iii)
optionally collecting body metric measurements; b) receiving from
said subject and via the digital interface, said subject-specific
data for one or more validated compliance parameters associated
with said therapeutic milestone; c) comparing entry activity
comprised of a rate and/or number of said subject-specific data
received from said subject via the digital interface with a
database of entry activity by prior subjects; and d) providing said
subject with milestone achievement input, wherein said milestone
achievement input is derived at least in part, or entirely, from
the entry activity (e.g., rate and/or number of subject-specific
data entry) received from said subject via said digital interface,
and predicts the subject's likelihood of success in achieving the
therapeutic milestone for said cardiometabolic disorder at a future
date. In some embodiments, the methods of treatment result in a
reduced dosage of one or more pharmaceutical interventions.
[0011] In another aspect, methods for reducing reliance on and/or
dosage of a pharmaceutical intervention in a subject having a
cardiometabolic disorder are provided, comprising a) providing to
said subject a digital interface for: i) receiving a lifestyle
intervention regimen to achieve a therapeutic milestone for said
cardiometabolic disorder; ii) entering subject-specific data for
one or more validated compliance parameters associated with said
therapeutic milestone for said cardiometabolic disorder; and iii)
optionally collecting body metric measurements; b) receiving from
said subject and via the digital interface, said subject-specific
data for one or more validated compliance parameters associated
with said therapeutic milestone; c) comparing entry activity
comprised of a rate and/or number of said subject-specific data
received from said subject via the digital interface with a
database of entry activity by prior subjects; d) providing said
subject with milestone achievement input, wherein said milestone
achievement input is derived at least in part, or entirely, from
the entry activity (e.g., rate and/or number of subject-specific
data entry) received from said subject via said digital interface,
and predicts the subject's likelihood of success in achieving the
therapeutic milestone for said cardiometabolic disorder at a future
date.
[0012] In another aspect, the present invention provides a method
for improving a lifestyle-related health condition in a subject by
a) providing to said subject a digital interface for: i) receiving
a lifestyle intervention regimen to achieve a lifestyle-related
health condition milestone; ii) entering subject-specific data for
one or more validated compliance parameters associated with said
lifestyle-related health condition milestone; and iii) optionally
collecting body metric measurements; b) monitoring entry of said
subject-specific data for one or more validated compliance
parameters associated with said lifestyle-related health condition
milestone by said subject and via the digital interface; c)
detecting an entry activity rate or amount that is below a
threshold; and d) sending a notification that triggers a user local
device to present a message to increase entry activity, wherein in
comparison to an absence of the monitoring, detecting, and sending,
the method: i) increases the subject's likelihood of adherence to
the lifestyle intervention program; ii) increases the subject's
likelihood of success in achieving the lifestyle-related health
condition milestone at a future date; iii) reduces reliance on one
or more pharmaceutical interventions in the subject; and/or iv)
provides a measurable improvement in one or more therapeutic
milestones.
[0013] In another aspect, the present invention provides a method
for improving a lifestyle-related health condition in a subject by
a) providing to said subject a digital interface for: i) receiving
a lifestyle intervention regimen to achieve a lifestyle-related
health condition milestone; ii) entering subject-specific data for
one or more validated compliance parameters associated with said
lifestyle-related health condition milestone; and iii) optionally
collecting body metric measurements; b) monitoring entry of said
subject-specific data for one or more validated compliance
parameters associated with said lifestyle-related health condition
milestone by said subject and via the digital interface; c)
detecting a failure to achieve or report achievement of one or more
validated compliance parameters; and d) sending a notification that
triggers a user local device to present a message to achieve or
report achievement of one or more validated compliance parameters,
wherein in comparison to an absence of the monitoring, detecting,
and sending, the method: i) increases the subject's likelihood of
adherence to the lifestyle intervention program; ii) increases the
subject's likelihood of success in achieving the lifestyle-related
health condition milestone at a future date; iii) reduces reliance
pharmaceutical on one or more pharmaceutical interventions in the
subject; and/or iv) provides a measurable improvement in one or
more therapeutic milestones.
[0014] In an exemplary embodiment of the above methods, the
cardiometabolic disorder is diabetes and the therapeutic milestone
comprises one or more of maintenance of HbA1c, fasting glucose,
fasting insulin, alanine transaminase, and/or fasting lipids at a
level indicative of therapeutic benefit for a subject having or at
risk of having diabetes. In some embodiments, the pharmaceutical
intervention(s) comprise one or more interventions selected from
the group consisting of: biguanides; sulfonylureas; meglitinide
derivatives; alpha-glucosidase inhibitors; thiazolidinediones
(TZDs); glucagonlike peptide-1 (GLP-1) agonists; dipeptidyl
peptidase IV (DPP-4) inhibitors; selective sodium-glucose
transporter-2 (SGLT-2) inhibitors, and insulin.
[0015] In another exemplary embodiment of the above methods, the
cardiometabolic disorder is heart disease and the therapeutic
milestone comprises one or more of weight loss, improved lipid
profile, lower blood pressure, and lower resting pulse rate. In
some embodiments, the pharmaceutical intervention(s) comprise one
or more interventions selected from the group consisting of: a
beta-blocking agent, an alpha-blocking agent, an
angiotensin-converting enzyme inhibitor, a statin, a diuretic, and
a calcium channel blocker.
[0016] In another exemplary embodiment, the cardiometabolic
disorder is hypertension and the therapeutic milestone comprises
maintenance of a diastolic and/or systolic blood pressure at a
level indicative of therapeutic benefit for a subject having or at
risk of having hypertension. In some embodiments, the
pharmaceutical intervention(s) comprise one or more interventions
selected from the group consisting of: a beta-blocking agent, an
alpha-blocking agent, an angiotensin-converting enzyme inhibitor,
an angiotensin II receptor blocker, a calcium channel blocker, a
diuretic, and a renin inhibitor.
[0017] In another exemplary embodiment, the cardiometabolic
disorder is hyperlipidemia and the therapeutic milestone is
improved lipid profile. In some embodiments, the pharmaceutical
intervention(s) comprise one or more interventions selected from
the group consisting of: a statin, exetimibe, and PCSK9
inhibitors.
[0018] In another exemplary embodiment, the cardiometabolic
disorder is coronary artery disease and the therapeutic milestone
comprises one or more of weight loss, improved lipid profile, lower
blood pressure, increased stamina, reduced angina, reduced fluid
retention, increased coronary arterial blood flow; and reduced
arterial plaque. In some embodiments, the pharmaceutical
intervention(s) comprise one or more interventions selected from
the group consisting of: a) a cholesterol-modifying medication
selected from the group consisting of a statin, exetimibe, and
PCSK9 inhibitors; b) an anti-coagulant, preferably selected from
the group consisting of an anti-platelet agent (e.g. aspirin or
Plavix), warfarin, low-molecular weight heparin, a direct thrombin
inhibitor, and a factor Xa inhibitor; c) a beta-blocking agent, d)
a vasodilator; e) a diuretic; and f) an angiotensin-converting
enzyme inhibitor and an angiotensin II receptor blocking agent.
[0019] In some embodiments of the foregoing aspects, the lifestyle
intervention regimen is selected from the group consisting of a
dietary regimen and an activity regimen, or a combination thereof.
In some cases, the lifestyle intervention regimen comprises a
dietary regimen, and said dietary regimen comprises a plant-based
diet. In some cases, the plant-based diet comprises, consists
essentially of, or consists of vegetables, fruit, legumes, nuts and
seeds, and whole grains. In some cases, the plant-based diet
comprises at least 50% of calories, or a majority of calories, from
vegetables, fruit, legumes, nuts and seeds, and whole grains. As
used herein, a plant-based diet consisting essentially of
vegetables, fruit, legumes, nuts and seeds, and whole grains is
comprised of at least 80% of calories from foods that are
categorized as a vegetable, fruit, legume, nut, seed, or whole
grains. Similarly, a plant-based diet consisting of vegetables,
fruit, legumes, nuts and seeds, and whole grains does not comprise
calories from animal-derived protein or fat, highly refined flour,
or added dietary sweeteners (e.g., sugar, cane syrup, etc.). In
some cases, the dietary regimen further comprises a culinary
literacy program comprising at least one of recipes, ingredients
and local ingredient acquisition locations. In some cases, the
validated compliance parameters comprise one or more compliance
parameters selected from the group consisting of: a) generate meal
plan; b) follow meal plan; c) procure ingredients from a shopping
list; d) engage with digital interface; e) log daily or weekly
targets (e.g. plant-based meals consumed, exercise performed); f)
log hydration; and/or g) communicate with coach.
[0020] In some embodiments of the foregoing aspects, the validated
compliance parameters comprise at least 2, 3, 4, 5, or 6, or all of
the compliance parameters selected from the group consisting of: a)
generate meal plan; b) follow meal plan; c) procure ingredients
from a shopping list; d) engage with digital interface; e) log
daily and/or weekly targets (e.g. plant-based meals consumed,
exercise performed); f) log hydration; and g) communicate with
coach.
[0021] In some embodiments of the foregoing aspects, the lifestyle
intervention comprises an activity regimen, and said activity
regimen comprises an exercise routine (e.g. type, frequency and
intensity of exercise), a daily caloric burn target, or a
combination thereof. In some cases, the validated compliance
parameters comprise compliance parameters selected from the group
consisting of: a) type of activity (e.g., resistance training,
interval training, flexibility training, cardiovascular training);
b) intensity of activity; c) duration of activity; d) frequency of
activity; e) engage with digital interface; f) log daily and/or
weekly targets (e.g. plant-based meals consumed, exercise
performed); g) log hydration; and h) communicate with coach. In
some cases, the lifestyle intervention further comprises the
dietary regimen.
[0022] In some embodiments of the foregoing aspects, the method
comprises collecting body weight metric measurements of said
subject via the digital interface and said milestone achievement
input is further derived from the body metric measurements of said
subject collected via the digital interface.
[0023] In some embodiments, the providing to said subject the
digital interface comprises transmitting the digital interface from
a digital interface server to a user local display. In some
embodiments, the user local display is a component of a user local
device, wherein said user local device comprises the user-local
display, a user local processor, and a user local datalink. In some
embodiments, the receiving from said subject said subject-specific
data comprises receiving one or more transmissions comprising said
subject-specific data: a) from said user local datalink; and b) to
a comparison engine.
[0024] In some embodiments, the providing said subject with
milestone achievement input comprises transmitting computer
readable instructions to said user-local device through said
user-local datalink, wherein said computer readable instructions
are configured to display a message comprising said input on said
user-local display. In some embodiments, the message comprises a
pre-configured communication indicating likelihood of success. In
some embodiments, the message comprises a pre-configured
communication encouraging increased engagement with the digital
interface (e.g., increased entry of subject-specific data). In some
embodiments, the message comprises a pre-configured communication
encouraging increased adherence to the lifestyle intervention
regimen.
[0025] In some embodiments, the milestone achievement input
comprises a communication (e.g., displayed by the digital
interface) that indicates likelihood of achieving a milestone. The
milestone achievement input can be in the form of a graphical icon
or a numerical score, or a combination thereof.
[0026] In some cases, the milestone achievement input communicates
a number, degree, or proportion by which the subject, in one or
more compliance parameters, has lagged prior individuals in the
database that successfully achieved the milestone, or has lagged a
population of prior individuals in the database, which population
of prior individuals is overrepresented by milestone achievers as
compared to the average individual.
[0027] In some cases, the milestone achievement input communicates
a number, degree, or proportion by which the subject, in one or
more compliance parameters, has lagged an average (mean or median)
of a population of prior individuals in the database that
successfully achieved the milestone, or has lagged a population of
prior individuals in the database, which population of prior
individuals is overrepresented by milestone achievers as compared
to the average individual. In some cases, the population is a
selected sub-population of prior individuals that is matched to a
subject's age, age range, gender, cardiometabolic disorder, body
mass index, or body mass index range.
[0028] In some embodiments, the milestone achievement input
comprises additional or alternative lifestyle interventions or
regimens for increasing the likelihood or degree of milestone
achievement, and/or increasing adherence to the lifestyle regimen.
In some embodiments, the milestone achievement input comprises
access to digital tools, e.g. for meal and/or exercise planning. In
some embodiments, the milestone achievement input further comprises
a request or requirement for confirmation or proof of completion of
such additional or alternative lifestyle interventions or regimens,
e.g. by photographic means.
[0029] In some embodiments, the milestone achievement input
comprises a care escalation protocol providing for and/or
scheduling a follow-up meeting with one or more human service
providers (e.g., health coach, dietician, nutritionist,
chef-educator, nurse practitioner, physical therapist,
kinesiologist, physician, behavioral psychologist, psychiatrist,
and the like). Additionally or alternatively, such care-escalation
protocols can include a suggestion to complete one or more
individual (one-on-one) or small-group coaching sessions with a
medical service provider (e.g., nurse practitioner, physical
therapist, kinesiologist, physician, behavioral psychologist,
psychiatrist, and the like).
[0030] In some cases, where a subject enters a low number, count,
rate, intensity, or entry activity of meal plan use; meal fallback;
shopping list use; or number of meal plan meals consumed, the
methods described herein can include a suggestion to complete one
or more individual (one-on-one) or small-group coaching sessions
with a health coach, dietician, nutritionist, chef-educator and/or
combinations thereof. In some cases, where a subject enters a low
number, count, rate, intensity, or entry activity of physical
activities prescribed by the lifestyle regime, the methods
described herein can include a suggestion to complete one or more
individual (one-on-one) or small-group coaching sessions with a
health coach, physical therapist, kinesiologist, and/or
combinations thereof. In related embodiments, the method further
comprises: step e) initiating direct personal feedback to said
subject or increasing the level of direct personal feedback
provided to said subject when said subject is predicted to be
likely to miss their milestone.
[0031] In some embodiments, and particularly where there has been
no or only limited engagement by the subject with the digital
interface, a notification that triggers a user local device to
present a messagefor interfacing with and/or encouraging dialogue
with an automated chat module (chatbot) is provided to the user
local device. In some embodiments, the automated chat module is
configured to increase adherence to the lifestyle intervention
regimen, e.g., via providing an interactive dialogue interface for
encouraging the subject to engage with the digital interface and/or
enter subject-specific data. In some embodiments, the automated
chat module is configured to increase rate or number of
subject-specific data entered by the subject via the digital
interface, e.g., via providing an interactive dialogue interface.
Chatbot technologies and their use are further described in
co-pending PCT application entitled "SYSTEMS, METHODS, AND
APPARATUSES FOR MANAGING DATA FOR ARTIFICIAL INTELLIGENCE SOFTWARE
AND MOBILE APPLICATIONS IN DIGITAL HEALTH THERAPEUTICS", Attorney
Docket No. BETR-002/PCT, filed Apr. 26, 2018.
[0032] In some embodiments, the lifestyle-related health condition
milestone or therapeutic milestone for said cardiometabolic
disorder comprises weight loss.
[0033] In some embodiments, the cardiometabolic disorder is
diabetes, and said therapeutic milestone comprises maintenance of
an HbA1c at a level indicative of therapeutic benefit for a subject
having or at risk of having type-II diabetes.
[0034] In some embodiments, the cardiometabolic disorder is heart
disease, and said therapeutic milestone comprises is selected from
the group consisting of: a) weight loss; b) improved lipid profile;
c) lower blood pressure; and d) lower resting pulse rate.
[0035] In another aspect, the present invention provides a system
for performing a method according to any one of the foregoing
aspects, embodiments, cases, or examples. In another aspect, the
present invention provides a computer readable medium for
performing a method according to any one of the foregoing aspects,
embodiments, cases, or examples.
INCORPORATION BY REFERENCE
[0036] All publications, patents, and patent applications mentioned
in this specification are herein incorporated by reference to the
same extent as if each individual publication, patent, or patent
application was specifically and individually indicated to be
incorporated by reference.
BRIEF DESCRIPTION OF THE FIGURES
[0037] FIG. 1 is a flow chart of an embodiment of a method for
improving a lifestyle-related health condition of a subject.
[0038] FIG. 2 is a flow chart of an embodiment of a method for
improving a lifestyle-related health condition of a subject.
[0039] FIG. 3 is a flow chart of an embodiment of a method for
treating a subject having or at risk of having a cardiometabolic
disorder.
[0040] FIG. 4 is a flow chart of an embodiment of a method for
treating a subject having or at risk of having a cardiometabolic
disorder.
[0041] FIG. 5 illustrates data from performing an embodiment of a
method disclosed herein. The data indicate that the number of
completed coaching calls entered into the digital interface is
positively correlated with a weight loss milestone.
[0042] FIG. 6 illustrates data from performing an embodiment of a
method disclosed herein. The data indicate that the number of
entries into the digital interface that indicate completion of an
activity target is positively correlated with a weight loss
milestone.
[0043] FIG. 7 illustrates data from performing an embodiment of a
method disclosed herein. In this embodiment, participant subjects
who entered via the digital interface an indication of
non-completion of an activity target, were provided an activity
fall back inquiry. The data indicate that participant subjects
accurately entered via the digital interface subject-specific data
for an activity fall back compliance parameter, as indicated by the
number of entries indicating a fall back activity was not
completed.
[0044] FIG. 8 illustrates data from performing an embodiment of a
method disclosed herein. The data indicate that the majority of
subjects who completed a lifestyle intervention regimen entered via
the digital interface subject-specific data indicating a high rate
and number of a meal-plan count compliance parameter.
[0045] FIG. 9 illustrates data from performing an embodiment of a
method disclosed herein. The data indicate that the number of
entries into the digital interface that indicate completion of a
meal target is positively correlated with a weight loss
milestone.
[0046] FIG. 10 illustrates data from performing an embodiment of a
method disclosed herein. In this embodiment, participant subjects
who entered via the digital interface an indication of
non-completion of a meal plan target, were provided a meal plan
fall back inquiry. The data indicate that more frequent logging of
consumption of meal plan fall backs via the digital interface is
positively correlated with weight loss.
[0047] FIG. 11 illustrates data from performing an embodiment of a
method disclosed herein. In this embodiment, participant subjects
entered via the digital interface an indication of non-completion
of a meal plan target, were provided a meal plan fall back inquiry.
The data indicate that more frequent logging of non-consumption of
meal plan fall backs via the digital interface is associated with a
reduced amount of weight loss.
[0048] FIG. 12 illustrates data from performing an embodiment of a
method disclosed herein. In this embodiment, participant subjects
entered via the digital interface an indication of water intake.
The data indicate that more frequent logging of water-intake via
the digital interface is positively correlated with weight
loss.
[0049] FIG. 13 illustrates data from performing an embodiment of a
method disclosed herein. In this embodiment, participant subjects
entered via the digital interface an indication that a provided
shopping list was used. The data indicate that more frequent
logging of shopping list use via the digital interface is
positively correlated with weight loss.
[0050] FIG. 14 illustrates data from performing an embodiment of a
method disclosed herein. In this embodiment, participant subjects
entered via the digital interface an indication that a body weight
check was performed. The data indicate that more frequent logging
of a weight check via the digital interface is positively
correlated with weight loss.
[0051] FIG. 15 illustrates data from performing an embodiment of a
method disclosed herein. The number of times participant subjects
engaged with the digital interface and entered at least one
subject-specific datapoint per week is depicted as a boxplot.
Participant subjects who completed the 16 week program exhibited a
high degree of engagement throughout the program.
[0052] FIG. 16 illustrates data from performing an embodiment of a
method disclosed herein. In this embodiment, participant subjects
entered via the digital interface a log of activity. Participants
who completed the lifestyle intervention regimen entered an average
of 4 activity days per week.
[0053] FIG. 17 illustrates data from performing an embodiment of a
method disclosed herein. The number of times participant subjects
entered a completed coaching call via the digital interface was
positively and strongly correlated with weight loss.
[0054] FIG. 18 illustrates data from performing an embodiment of a
method disclosed herein. Logged activity data entered via the
digital interface were divided into four equal sized quartiles.
More frequent logging of activity via the digital interface was
positively correlated with weight loss.
[0055] FIG. 19 illustrates data from performing an embodiment of a
method disclosed herein. Meal plan use data entered via the digital
interface were divided into four equal sized quartiles. More
frequent logging of meal plan use via the digital interface was
positively correlated with weight loss. Participant subjects who
logged the most meal plan utilization lost approximately twice as
much weight as those who logged the least.
[0056] FIG. 20 illustrates data from performing an embodiment of a
method disclosed herein. Water-intake count data entered via the
digital interface were divided into four equal sized quartiles.
More frequent logging of water-intake via the digital interface was
positively correlated with weight loss. Participant subjects who
logged the most water-intake lost approximately twice as much
weight as those who logged the least.
[0057] FIG. 21 illustrates data from performing an embodiment of a
method disclosed herein. Body weight check activity data entered
via the digital interface were divided into four equal sized
quartiles. More frequent logging via the digital interface of
performance of a body weight check was positively correlated with
weight loss.
[0058] FIG. 22 compares the change in hemoglobin A1c and weight by
tertile of engagement in subset of participants with baseline
HbA1c>7.0% and no mid-study medication changes. Bars represent
means and standard errors. Star indicates P=0.03 between
groups.
[0059] FIG. 23 illustrates therapeutic milestone achievement in
subjects participating in extended (>12 weeks) diabetes
treatment study.
[0060] FIG. 24 illustrates therapeutic milestone achievement in
subjects participating in hypertension treatment study.
DETAILED DESCRIPTION OF THE INVENTION
[0061] The present invention relates to methods and systems for
improving a lifestyle-related health condition of a subject. An
exemplary lifestyle-related health condition is body weight.
However, the methods and systems described herein can be applied to
improve a variety of different lifestyle-related health conditions
as well as particular cardiometabolic disorders for which the
patient may already be undergoing clinical treatment.
Cardiometabolic disorders that may be effectively targeted and
treated by way of the subject invention include, e.g. metabolic
disorders such as hyperglycemia, diabetes and the like as well as
cardiovascular diseases such as hypertension, hyperlipidemia,
angina, and the like.
[0062] In some embodiments, a method 100 is provided, including
step 110 providing to a subject a digital interface. Typically, the
digital interface is displayed on a user-local device. As used
herein "user-local" device refers to a device that is owned or in
physical possession of the subject. In some cases, the digital
interface is provided by transmitting instructions to display the
digital interface from a remote server to the user-local device. In
other cases, the instructions to display the digital interface can
be stored on the user-local device. In yet other cases, a portion
of the instructions to display the digital interface can be stored
on the user-local device, and a portion of the instructions
transmitted to the user-local device from a remote server. The
instructions can be stored and/or transmitted in the form of
transitory or non-transitory computer readable media.
[0063] The digital interface of this embodiment is configured to
receive subject-specific data for one or more validated compliance
parameters that is entered by the subject via the digital
interface. The validated compliance parameters can be validated as
associated with a lifestyle-related health condition milestone. The
lifestyle-related health condition milestone can be an improvement
in a lifestyle-related health condition, or a target level of
improvement in a lifestyle-related health condition. In some cases,
the lifestyle-related health condition milestone is selected by the
subject via the digital interface. In other cases, the
lifestyle-related health condition milestone is pre-selected by the
digital interface provider.
[0064] The method can further include a step 115b, in which a
subject enters subject-specific data for one or more validated
compliance parameters. Such data can include one or more of the
following: whether a meal plan was followed; whether a lifestyle
regimen activity was completed; whether a coaching call was
completed; whether one or more, or all, ingredients on a shopping
list were procured; whether the subject consumed a specified amount
of water or whether the subject consumed water; a number of
plant-based meals consumed, a number of exercise activities
completed, the length of exercise activities completed (e.g.
minutes of daily or weekly exercise), a number of coaching calls
completed, length of one or more coaching calls, a number or
fraction of ingredients procured from a shopping list, a number of
hydration events, or a total volume of hydration. In some cases,
where a meal plan was not followed, the data can include whether a
meal fallback was consumed. In some cases, exercise data can
include type of activity completed, e.g., resistance training,
interval training, flexibility training, or cardiovascular
training. In some cases, exercise data can include sub-type of
activity completed, e.g., running, walking, swimming, weight
lifting, yoga, etc. In some cases, data can include number or
frequency of body weight measurements performed.
[0065] In preferred embodiments, the dietary regimens employed in
the subject methods comprise, consist essentially of, or consist of
a plant-based diet, i.e., they include one or more ingredients
taken from the general classes of vegetables, fruits, legumes,
whole grains, and/or nuts and seeds, the beneficial clinical impact
of which has been well established. See, e.g., Jenkins et al., A
dietary portfolio approach to cholesterol reduction: combined
effects of plant sterols, vegetable proteins, and viscous fibers in
hypercholesterolemia Metabolism 51:1596-1604 (2002); Barnard et
al., A low-fat vegan diet and a conventional diabetes diet in the
treatment of type 2 diabetes: a randomized, controlled, 74-wk
clinical trial Am J Clin Nutr 89:15885-15968 (2009). In some
embodiments, the plant-based diet comprises at least 50% of
calories, or a majority of calories, from the foregoing general
classes of vegetables, fruits, legumes, whole grains, and/or nuts
and seeds. In some embodiments, the plant-based diet consists or
consists essentially of vegetables, fruit, legumes, nuts and seeds,
and whole grains. In some embodiments, where a meal plan focuses
primarily on one class of ingredient, e.g., a vegetable or a
legume, suitable meal fallbacks will be selected from among the
remaining classes of ingredients, e.g., fruits, whole grains and/or
nuts and seeds. As demonstrated herein the predictive value of
non-compliance with a given meal plan is further enhanced by
determining adherence to the preferred dietary principles, i.e.
following a plant-based diet, by way of fall back inquiries.
[0066] In some cases, the data can be received, stored, and/or
transmitted as a Boolean variable (e.g., true or false). For
example, meal plan use data can be stored as a true indicating a
meal plan was used (i.e., the meal specified by the meal plan was
consumed) or a false indicating that a meal plan was not used
(i.e., the meal specified by the meal plan was not consumed). In
some cases, the data can be received, stored, and/or transmitted as
a numerical variable (e.g., number of exercise activities
completed, total amount of time engaged in one or more exercise
activities, number of meals consumed, or number of coaching calls
completed).
[0067] In an optional step 115c, that may be present or absent in
this embodiment, the subject enters one or more body metric
measurements. The one or more body metric measurements can be or
include body weight, lipid profile, cholesterol level, triglyceride
levels, low-density lipoprotein level, high-density lipoprotein
level, very low-density lipoprotein level, blood pressure, fasting
blood glucose level, pre-prandial glucose level; post-prandial
glucose level, blood insulin level, fasting insulin level, alanine
transaminase level, blood GIP level, insulin resistance, or
glycated hemoglobin (HbA1c) level.
[0068] The method can further include a step 120, in which the
subject-specific data entered into the digital interface by the
subject is received. In some embodiments, the subject-specific
data, or a portion thereof, is transmitted from the user-local
device and received by a remote server. In some cases, the remote
server includes a comparison engine. In some cases, the remote
server transmits the subject-specific data or a component thereof
to a comparison engine. The method can further include 135,
comparing a rate or number of the subject specific data with a
database of entry activity by prior subjects.
[0069] The comparison engine can output a prediction of likelihood
of milestone achievement based on the entry activity by prior
subjects. The likelihood can be determined as a function of
engagement with the digital interface (i.e., number of times a
subject has entered one or more, or all, subject-specific data),
engagement with the lifestyle regimen (i.e., rate of compliance
with lifestyle regimen activities, meal plans and the like). The
likelihood can be determined as a function of one or more
compliance parameters (e.g., true, false, number, or rate). For
example, the likelihood can be determined as a function of whether
a meal plan was followed or logged; or if not, whether a meal
fallback was consumed or logged; whether a lifestyle regimen
activity was completed or logged; whether a coaching call was
completed or logged; whether ingredients on a lifestyle regimen
shopping list were procured or logged; whether the subject consumed
a specified amount of water or whether water intake was logged; a
number of plant-based meals consumed, a number of exercise
activities completed, the length of exercise activities completed
(e.g. minutes of daily or weekly exercise), a number of coaching
calls completed, length of one or more coaching calls, a number or
fraction of ingredients procured from a shopping list, a number of
hydration events, a total volume of hydration logged, or a number
or rate of body weight measurements performed. In some cases, the
likelihood can be determined as a function of type, duration,
frequency and/or intensity of exercise completed and/or logged.
[0070] In some cases, the likelihood is determined by a
multi-factorial weighted analysis of two or more, three or more,
four or more, five or more, six or more, seven or more, eight or
more, or all types, amounts, or rates of entry activity sub-types
(e.g., engagement with interface, engagement with lifestyle
regimen, compliance parameters, and/or type, frequency, duration
and/or intensity of exercise completed). The weights and activity
sub-types can be identified manually, by trial and error, or
computationally via, e.g., logistic regression or machine learning,
methods to identify patterns associated with a high or low
likelihood of therapeutic milestone achievement.
[0071] For example, if a subject enters a low number of
subject-specific datapoints (e.g., either relative to other members
of the subject cohort, or relative to prior subjects in the
database, or a portion thereof) into the digital interface, the
comparison engine can indicate that the subject is unlikely to
achieve a lifestyle-related health condition milestone. As another
example, if a subject enters a high number of subject-specific
datapoints into the digital interface, the comparison engine can
indicate that the subject is likely to achieve a lifestyle-related
health condition milestone.
[0072] As yet another example, if a subject enters into the digital
interface a high number of meal plan meals consumed, the comparison
engine can indicate that the subject is likely to achieve a
lifestyle-related health condition milestone. As yet another
example, if a subject enters into the digital interface a low
number of meal plan meals consumed, the comparison engine can
indicate that the subject is unlikely to achieve a
lifestyle-related health condition milestone. As yet another
example, if a subject enters into the digital interface a high
number of meal fallbacks consumed, the comparison engine can
indicate that the subject is likely to achieve a lifestyle-related
condition health milestone. As yet another example, if a subject
enters into the digital interface a low number of meal fallbacks
consumed, the comparison engine can indicate that the subject is
unlikely to achieve a lifestyle-related health condition
milestone.
[0073] As yet another example, if a subject enters into the digital
interface a high number of completed coaching calls, the comparison
engine can indicate that the subject is likely to achieve a
lifestyle-related health condition milestone. As yet another
example, if a subject enters into the digital interface a low
number of completed coaching calls, the comparison engine can
indicate that the subject is unlikely to achieve a
lifestyle-related health condition milestone. As yet another
example, if a subject enters into the digital interface a high
number or length of completed exercise activities, the comparison
engine can indicate that the subject is likely to achieve a
lifestyle-related health condition milestone. As yet another
example, if a subject enters into the digital interface a low
number or length of completed exercise activities, the comparison
engine can indicate that the subject is unlikely to achieve a
lifestyle-related health condition milestone.
[0074] As yet another example, if a subject enters into the digital
interface a high number of meal water-intake events, the comparison
engine can indicate that the subject is likely to achieve a
lifestyle-related health condition milestone. As yet another
example, if a subject enters into the digital interface a low
number of water-intake events, the comparison engine can indicate
that the subject is unlikely to achieve a lifestyle-related health
condition milestone. As yet another example, if a subject enters
into the digital interface a high volume of water intake, the
comparison engine can indicate that the subject is likely to
achieve a lifestyle-related health condition milestone. As yet
another example, if a subject enters into the digital interface a
low volume of water-intake, the comparison engine can indicate that
the subject is unlikely to achieve a lifestyle-related health
condition milestone.
[0075] As yet another example, if a subject enters into the digital
interface a high number of shopping list ingredients procured, the
comparison engine can indicate that the subject is likely to
achieve a lifestyle-related health condition milestone. As yet
another example, if a subject enters into the digital interface a
low number of number of shopping list ingredients procured, the
comparison engine can indicate that the subject is unlikely to
achieve a lifestyle-related health condition milestone. As yet
another example, if a subject enters into the digital interface a
high count of body weight measurement activities, the comparison
engine can indicate that the subject is likely to achieve a
lifestyle-related health condition milestone. As yet another
example, if a subject enters into the digital interface a low count
of body weight measurement activities, the comparison engine can
indicate that the subject is unlikely to achieve a
lifestyle-related health condition milestone.
[0076] In preferred embodiments, the prediction is a function of 2,
3, 4, 5, 6, 7, 8, 9, 10, or more of a number, count, rate,
intensity, or entry activity of meal plan use; meal fallback;
activity; coaching call; shopping list use; water-intake; a number
of meal plan meals consumed, or a body weight measurement.
[0077] The method can further include 140, providing the subject
with milestone achievement input. The milestone achievement input
can be a communication (e.g., displayed by the digital interface)
that indicates likelihood of achieving the lifestyle-related health
condition milestone. The milestone achievement input can be in the
form of a graphical icon or a numerical score, a pre-configured
message, or a combination thereof. The milestone achievement input
can suggest additional or alternative lifestyle interventions or
regimens for increasing the likelihood or degree of milestone
achievement. In some case, the milestone achievement input
communicates a number, degree, or proportion by which the subject,
in one or more compliance parameters, has lagged prior individuals
in the database that successfully achieved the milestone, or has
lagged a population of prior individuals in the database, which
population of prior individuals is overrepresented by milestone
achievers as compared to the average individual.
[0078] For example in some embodiments, coaching call completion
shows a strong positive correlation with weight loss. In this case,
a subject who has entered a low number of completed coaching calls
via a digital interface can be predicted as unlikely to achieve the
weight loss milestone. The milestone achievement input can suggest
completing more coaching calls, or indicate the difference between
coaching calls completed by the subject and coaching calls
completed by the highest weight loss quartile of the prior
individuals in the database, or provide for and/or schedule a
follow-up meeting with one or more human service providers (e.g.,
health coach, dietician, nutritionist, chef-educator, nurse
practitioner, physical therapist, kinesiologist, physician,
behavioral psychologist, psychiatrist, and the like). Such
care-escalation protocols can include a suggestion to complete one
or more individual (one-on-one) or small-group coaching sessions
with a medical provider (e.g., nurse practitioner, physical
therapist, kinesiologist, physician, behavioral psychologist,
psychiatrist, or a combination thereof). In some cases, where a
subject enters a low number, count, rate, intensity, or entry
activity of meal plan use; meal fallback; shopping list use; or
number of meal plan meals consumed, the methods described herein
can include a suggestion to complete one or more individual
(one-on-one) or small-group coaching sessions with a health coach,
nutritionist, dietician, and/or chef-educator. In this way, more
time-consuming and/or expensive human resources and/or personal
medical care can be more efficiently implemented in escalating
fashion when needed in order to assist the subject with their
milestone achievement, and is not utilized with individuals who are
likely to reach their milestone achievement in any event.
[0079] The milestone achievement input can be a communication
(e.g., displayed by the digital interface) that is configured to
increase engagement with the digital interface. For example, the
communication can request entry of subject-specific data for one or
more compliance parameters. In some embodiments, the method can
include monitoring entry activity for one or more compliance
parameters, detecting an absence of entry activity or an entry
activity that is below a threshold and providing a milestone
achievement input that requests or encourages entry activity. In
some embodiments, the method can include monitoring entry activity
for one or more compliance parameters, detecting an absence of
entry activity indicating completion of one or more compliance
parameters or an entry activity indicating completion of one or
more compliance parameters that is below a threshold and providing
a milestone achievement input that requests or encourages entry
activity, and/or requests or encourages completion of one more
compliance parameters.
[0080] In an exemplary embodiment, a subject that fails to report
completion of a meal plan or completion of a threshold number of
meal plans specified in the lifestyle intervention regimen, can be
provided a milestone achievement input encouraging the subject to
complete one or more meal-plans and/or enter meal-plans into the
digital interface. In another exemplary embodiment, a subject that
fails to report either completion or non-completion of a meal plan
or a threshold number of meal plans specified in the lifestyle
intervention regimen, can be provided a milestone achievement input
instructing the subject to enter meal-plans into the digital
interface.
[0081] Similarly, a subject that fails to report, via the digital
interface, completion of a length of activity or number of exercise
activities or completion of a threshold number or length of
exercise activity specified in the lifestyle intervention regimen,
can be provided a milestone achievement input encouraging the
subject to complete one or more exercise activities and/or enter
exercise activity into the digital interface. In another exemplary
embodiment, a subject that fails to report either completion or
non-completion of exercise activity or a threshold number or length
of exercise activities specified in the lifestyle intervention
regimen, can be provided a milestone achievement input instructing
the subject to enter exercise activity. In some cases, the
milestone achievement input increases adherence to the lifestyle
intervention regiment as compared to a method that does not provide
such milestone achievement input.
[0082] In some embodiments the method or portions thereof is
repeated one or more times. For example, after receiving the
subject-specific data 120, the digital interface 110 can be
provided to the subject for entry into the digital interface of
subject specific data for one or more validated compliance
parameters. Additionally or alternatively, the method can be
repeated after the comparing step of 135. Additionally or
alternatively, the method can be repeated after the providing step
of 140. The repeating can be at a set frequency, such as hourly,
daily, weekly, etc. (e.g., throughout the duration of the lifestyle
intervention regimen). Alternatively, the repeating can be for a
set number of times throughout the duration of the lifestyle
intervention regimen. For example, the method can provide the
digital interface for entry of subject-specific data about 2, 3, 4,
5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or more times for the
duration of the lifestyle intervention regimen. As another example,
the repeating can be on a continual basis or initiated by the
subject's access of the digital interface on the user-local
device.
[0083] In some embodiments, a method 200 is provided, including a
step 210 providing to a subject a digital interface as described
herein. Typically, the digital interface is displayed on a
user-local device. In some cases, the digital interface is provided
by transmitting instructions to display the digital interface from
a remote server to the user-local device. In other cases, the
instructions to display the digital interface can be stored on the
user-local device. In yet other cases, a portion of the
instructions to display the digital interface can be stored on the
user-local device, and a portion of the instructions transmitted to
the user-local device from a remote server. The instructions can be
stored and/or transmitted in the form of transitory or
non-transitory computer readable media.
[0084] The digital interface of this embodiment is configured to
receive subject-specific data for one or more validated compliance
parameters that is entered by the subject via the digital
interface. The validated compliance parameters can be validated as
associated with a lifestyle-related health condition milestone. The
lifestyle-related health condition milestone can be an improvement
in a lifestyle-related health condition, or a target level of
improvement in a lifestyle-related health condition. In some cases,
the lifestyle-related health condition milestone is selected by the
subject via the digital interface. In other cases, the
lifestyle-related health condition milestone is pre-selected by the
digital interface provider.
[0085] The method can further include a step 215a, in which a
subject receives from the digital interface a lifestyle
intervention regimen. Typically, the lifestyle intervention regimen
is displayed as a series of lifestyle activities (e.g., diet or
meal plans, exercise plans, hydration instructions, etc.) or
provided as a file containing the series of lifestyle
activities.
[0086] The method can further include a step 215b, in which a
subject enters subject-specific data for one or more validated
compliance parameters. Such data can include one or more of the
following: whether a meal plan was followed; whether a lifestyle
regimen activity was completed; whether a coaching call was
completed; whether one or more, or all, ingredients on a shopping
list were procured; whether the subject consumed a specified amount
of water or whether the subject consumed water; a number of meal
plan meals consumed, a number of exercise activities completed, a
total amount time (e.g., minutes) engaged in one or more exercise
activities, a number of coaching calls completed, length of one or
more coaching calls, a number or fraction of ingredients procured
from a shopping list, a number of hydration events, or a total
volume of hydration. In some cases, where a meal plan was not
followed, the data can include whether a meal fallback was
consumed. In some cases, data can include type or amount of
physical activity completed and/or logged. In some cases, data can
include number or frequency of body weight measurements
performed.
[0087] In some cases, the data can be received, stored, and/or
transmitted as a Boolean variable (e.g., true or false). For
example, meal plan use data can be stored as a true indicating a
meal plan was used (i.e., the meal specified by the meal plan was
consumed) or a false indicating that a meal plan was not used
(i.e., the meal specified by the meal plan was not consumed). In
some cases, the data can be received, stored, and/or transmitted as
a numerical variable (e.g., total amount of time (e.g., minutes)
engaged in one or more exercise activities, number of exercise
activities completed, number of meals consumed, or number of
coaching calls completed).
[0088] In an optional step 215c, that may be present or absent in
this embodiment, the subject enters one or more body metric
measurements. The one or more body metric measurements can be or
include body weight, lipid profile, cholesterol level, triglyceride
levels, low-density lipoprotein level, high-density lipoprotein
level, very low-density lipoprotein level, blood pressure, fasting
blood glucose level, pre-prandial blood glucose level,
post-prandial blood glucose level, blood insulin level, fasting
insulin level, blood alanine transaminase level, blood GIP level,
insulin resistance, or glycated hemoglobin (HbA1c) level.
[0089] The method can further include a step 220, in which the
subject-specific data entered into the digital interface by the
subject is received. In some embodiments, the subject-specific
data, or a portion thereof, is transmitted from the user-local
device and received by a remote server. In some cases, the remote
server includes a comparison engine. In some cases, the remote
server transmits the subject-specific data or a component thereof
to a comparison engine. The method can further include 235,
comparing a rate or number of the subject specific data with a
database of entry activity by prior subjects.
[0090] The comparison engine can output a prediction of likelihood
of milestone achievement based on the entry activity by prior
subjects. The likelihood can be determined as a function of
engagement with the digital interface (i.e., number of times a
subject has entered one or more, or all, subject-specific data),
engagement with the lifestyle regimen (i.e., rate of compliance
with lifestyle regimen activities, meal plans and the like). The
likelihood can be determined as a function of one or more
compliance parameters (e.g., true, false, number, or rate). For
example, the likelihood can be determined as a function of whether
a meal plan was followed or logged; or if not, whether a meal
fallback was consumed or logged; whether a lifestyle regimen
activity was completed or logged; whether a coaching call was
completed or logged; whether ingredients on a lifestyle regimen
shopping list were procured or logged; whether the subject consumed
a specified amount of water or whether water-intake was logged; a
number of meal plan meals consumed, a number of activities
completed, a total amount of time (e.g., minutes) engaged in one or
more activities, a number of coaching calls completed, length of
one or more coaching calls, a number or fraction of ingredients
procured from a shopping list, a number of hydration events, a
total volume of hydration logged, or a number or rate of body
weight measurements performed. In some cases, the likelihood can be
determined as a function of type, frequency, duration, and/or
intensity of exercise completed and/or logged.
[0091] In preferred embodiments, the prediction is a function of 2,
3, 4, 5, 6, 7, 8, 9, 10, or more of a number, count, rate,
intensity, length of, or entry activity of meal plan use; meal
fallback; physical activity; coaching call; shopping list use;
water-intake; a number of meal plan meals consumed, or a body
weight measurement.
[0092] The method can further include 240, providing the subject
with milestone achievement input. The milestone achievement input
can be a communication (e.g., displayed by the digital interface)
that indicates likelihood of achieving a milestone. The milestone
achievement input can be in the form of a graphical icon or a
numerical score, or a combination thereof.
[0093] The milestone achievement input can suggest additional or
alternative lifestyle interventions or regimens for increasing the
likelihood or degree of milestone achievement. In some case, the
milestone achievement input communicates a number, degree, or
proportion by which the subject, in one or more compliance
parameters, has lagged prior individuals in the database that
successfully achieved the milestone, or has lagged a population of
prior individuals in the database, which population of prior
individuals is overrepresented by milestone achievers as compared
to the average individual.
[0094] In some cases, the milestone achievement input communicates
a number, degree, or proportion by which the subject, in one or
more compliance parameters, has lagged an average (mean or median)
of a population of prior individuals in the database that
successfully achieved the milestone, or has lagged in the database,
which population of prior individuals is overrepresented by
milestone achievers as compared to the average individual. In some
cases, the population is a selected sub-population of prior
individuals that is matched to a subject's age, age range, gender,
cardiometabolic disorder, body mass index, or body mass index
range.
[0095] In some cases, the milestone achievement input can suggest
or provide for and/or schedule a follow-up meeting with one or more
human service providers (e.g., health coach, dietician,
nutritionist, chef-educator, nurse practitioner, physical
therapist, kinesiologist, physician, behavioral psychologist,
psychiatrist, and the like). Such care-escalation protocols can
include a suggestion to complete one or more individual
(one-on-one) or small-group coaching sessions with a medical
service provider (e.g., nurse practitioner, physical therapist,
kinesiologist, physician, behavioral psychologist, psychiatrist,
and the like). In some cases, where a subject enters a low number,
count, rate, intensity, or entry activity of meal plan use; meal
fallback; shopping list use; or number of meal plan meals consumed,
the methods described herein can include a suggestion to complete
one or more individual (one-on-one) or small-group coaching
sessions with a health coach, dietician, nutritionist,
chef-educator and/or combinations thereof.
[0096] The milestone achievement input can be a communication
(e.g., displayed by the digital interface) that is configured to
increase engagement with the digital interface. For example, the
communication can request entry of subject-specific data for one or
more compliance parameters. In some embodiments, the method can
include monitoring entry activity for one or more compliance
parameters, detecting an absence of entry activity or an entry
activity that is below a threshold and providing a milestone
achievement input that requests or encourages entry activity. In
some embodiments, the method can include monitoring entry activity
for one or more compliance parameters, detecting an absence of
entry activity indicating completion of one or more compliance
parameters or an entry activity indicating completion of one or
more compliance parameters that is below a threshold and providing
a milestone achievement input that requests or encourages entry
activity, and/or requests or encourages completion of one more
compliance parameters.
[0097] In some embodiments the method or portions thereof is
repeated one or more times. For example, after receiving the
subject-specific data 220, the digital interface 210 can be
provided to the subject for entry into the digital interface of
subject specific data for one or more validated compliance
parameters. Additionally or alternatively, the method can be
repeated after the comparing step of 235. Additionally or
alternatively, the method can be repeated after the providing step
of 240. The repeating can be at a set frequency, such as hourly,
daily, weekly, etc. (e.g., throughout the duration of the lifestyle
intervention regimen). Alternatively, the repeating can be for a
set number of times throughout the duration of the lifestyle
intervention regimen. For example, the method can provide the
digital interface for entry of subject-specific data about 2, 3, 4,
5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or more times for the
duration of the lifestyle intervention regimen. As another example,
the repeating can be on a continual basis or initiated by the
subject's access of the digital interface on the user-local
device.
[0098] In some embodiments, a method 300 is provided, including
step 310 providing a digital interface to a subject having or at
risk of having a cardiometabolic disorder. Typically, the digital
interface is displayed on a user-local device. In some cases, the
digital interface is provided by transmitting instructions to
display the digital interface from a remote server to the
user-local device. In other cases, the instructions to display the
digital interface can be stored on the user-local device. In yet
other cases, a portion of the instructions to display the digital
interface can be stored on the user-local device, and a portion of
the instructions transmitted to the user-local device from a remote
server. The instructions can be stored and/or transmitted in the
form of transitory or non-transitory computer readable media.
[0099] The digital interface of this embodiment is configured to
receive subject-specific data for one or more validated compliance
parameters that is entered by the subject via the digital
interface. The validated compliance parameters can be validated as
associated with a therapeutic milestone for a specified
cardiometabolic disorder that a subject has or is at risk of
having. The therapeutic milestone can be an improvement in
cardiometabolic health condition, or a target level of improvement
in a cardiometabolic health condition. In some cases, the
therapeutic milestone for the cardiometabolic disorder is selected
by the subject via the digital interface. In other cases, the
therapeutic milestone for the cardiometabolic disorder is
pre-selected by the digital interface provider or a reference
physician.
[0100] The method can further include a step 315b, in which a
subject enters subject-specific data for one or more validated
compliance parameters. Such data can include one or more of the
following: whether a meal plan was followed; whether a lifestyle
regimen activity was completed; whether a coaching call was
completed; whether one or more, or all, ingredients on a shopping
list were procured; whether the subject consumed a specified amount
of water or whether the subject consumed water; a number of meal
plan meals consumed, a number of activities completed, a total
amount of time (e.g., minutes) engaged in one or more activities, a
number of coaching calls completed, length of one or more coaching
calls, a number or fraction of ingredients procured from a shopping
list, a number of hydration events, or a total volume of hydration.
In some cases, where a meal plan was not followed, the data can
include whether a meal fallback was consumed. In some cases, data
can include type, frequency and/or intensity of exercise completed
and/or logged. In some cases, data can include number or frequency
of body weight measurements performed.
[0101] In preferred embodiments, the dietary regiments employed in
the subject methods comprise, consist essentially of or consist of
a plant-based diet, i.e., they preferably comprise one or more
ingredients taken from the general classes of vegetables, fruits,
legumes, whole grains, and/or nuts and seeds.
[0102] In some cases, the data can be received, stored, and/or
transmitted as a Boolean variable (e.g., true or false). For
example, meal plan use data can be stored as a true indicating a
meal plan was used (i.e., the meal specified by the meal plan was
consumed) or a false indicating that a meal plan was not used
(i.e., the meal specified by the meal plan was not consumed). In
some cases, the data can be received, stored, and/or transmitted as
a numerical variable (e.g., amount of time engaged in one or more
exercise activities, number of meals consumed, or number of
coaching calls completed).
[0103] In an optional step 315c, that may be present or absent in
this embodiment, the subject enters one or more body metric
measurements. The one or more body metric measurements can be or
include body weight, lipid profile, cholesterol level, triglyceride
levels, low-density lipoprotein level, high-density lipoprotein
level, very low-density lipoprotein level, blood pressure, fasting
blood glucose level, pre-prandial blood glucose level,
post-prandial blood glucose level, blood insulin level, blood GIP
level, insulin resistance, or glycated hemoglobin (HbA1c)
level.
[0104] The method can further include a step 320, in which the
subject-specific data entered into the digital interface by the
subject is received. In some embodiments, the subject-specific
data, or a portion thereof, is transmitted from the user-local
device and received by a remote server. In some cases, the remote
server includes a comparison engine. In some cases, the remote
server transmits the subject-specific data or a component thereof
to a comparison engine. The method can further include 335,
comparing a rate or number of the subject specific data with a
database of entry activity by prior subjects.
[0105] The comparison engine can output a milestone achievement
input such as a prediction of likelihood of achievement of the
therapeutic milestone for the cardiometabolic disorder based on the
entry activity by prior subjects. The milestone achievement input
(e.g., likelihood of achievement of therapeutic milestone) can be
determined as a function of engagement with the digital interface
(i.e., number of times a subject has entered one or more, or all,
subject-specific data), engagement with the lifestyle regimen
(i.e., rate of compliance with lifestyle regimen activities, meal
plans and the like). The milestone achievement input can be
determined as a function of one or more compliance parameters
(e.g., true, false, number, or rate). For example, the milestone
achievement input can be determined as a function of whether a meal
plan was followed or logged; or if not, whether a meal fallback was
consumed or logged; whether a lifestyle regimen activity was
completed or logged; whether a coaching call was completed or
logged; whether ingredients on a lifestyle regimen shopping list
were procured or logged; whether the subject consumed a specified
amount of water or whether water-intake was logged; a number of
meal plan meals consumed, a number of activities completed, a total
amount of time engaged in one or more exercise activities, a number
of coaching calls completed, length of one or more coaching calls,
a number or fraction of ingredients procured from a shopping list,
a number of hydration events, a total volume of hydration logged,
or a number or rate of body weight measurements performed. In some
cases, the ilestone achievement inputcan be determined as a
function of type, frequency and/or intensity of exercise completed
and/or logged.
[0106] For example, if a subject enters a low number of
subject-specific datapoints (e.g., either relative to other members
of the subject cohort, or relative to prior subjects in the
database, or a portion thereof such as a matched sub-population of
prior subjects) into the digital interface, the comparison engine
can indicate that the subject is unlikely to achieve a therapeutic
milestone. As another example, if a subject enters a high number of
subject-specific datapoints into the digital interface, the
comparison engine can indicate that the subject is likely to
achieve a therapeutic milestone. As another example, if a subject
enters a low number of subject-specific datapoints, or a low number
of datapoints indicating successful completion of dietary and/or
exercise activities specified in the lifestyle intervention
regimen, the comparison engine can provide a milestone achievement
input requesting or encouraging additional entry activity and/or
requesting or encouraging additional completion and entry of
activities specified in the lifestyle intervention regimen.
[0107] As yet another example, if a subject enters into the digital
interface a high number of meal plan meals consumed, the comparison
engine can indicate that the subject is likely to achieve a
therapeutic milestone. As yet another example, if a subject enters
into the digital interface a low number of meal plan meals
consumed, the comparison engine can indicate that the subject is
unlikely to achieve a therapeutic milestone. As yet another
example, if a subject enters into the digital interface a high
number of meal fallbacks consumed, the comparison engine can
indicate that the subject is likely to achieve a therapeutic
milestone. As yet another example, if a subject enters into the
digital interface a low number of meal fallbacks consumed, the
comparison engine can indicate that the subject is unlikely to
achieve a therapeutic milestone.
[0108] As yet another example, if a subject enters into the digital
interface a high number of completed coaching calls, the comparison
engine can indicate that the subject is likely to achieve a
therapeutic milestone. As yet another example, if a subject enters
into the digital interface a low number of completed coaching
calls, the comparison engine can indicate that the subject is
unlikely to achieve a therapeutic milestone. As yet another
example, if a subject enters into the digital interface a high
number of completed activities, the comparison engine can indicate
that the subject is likely to achieve a therapeutic milestone. As
yet another example, if a subject enters into the digital interface
a low number of completed activities, the comparison engine can
indicate that the subject is unlikely to achieve a therapeutic
milestone.
[0109] As yet another example, if a subject enters into the digital
interface a high number of meal water-intake events, the comparison
engine can indicate that the subject is likely to achieve a
therapeutic milestone. As yet another example, if a subject enters
into the digital interface a low number of water-intake events, the
comparison engine can indicate that the subject is unlikely to
achieve a therapeutic milestone. As yet another example, if a
subject enters into the digital interface a high volume of water
intake, the comparison engine can indicate that the subject is
likely to achieve a therapeutic milestone. As yet another example,
if a subject enters into the digital interface a low volume of
water-intake, the comparison engine can indicate that the subject
is unlikely to achieve a therapeutic milestone.
[0110] As yet another example, if a subject enters into the digital
interface a high number of shopping list ingredients procured, the
comparison engine can indicate that the subject is likely to
achieve a therapeutic milestone. As yet another example, if a
subject enters into the digital interface a low number of number of
shopping list ingredients procured, the comparison engine can
indicate that the subject is unlikely to achieve a therapeutic
milestone. As yet another example, if a subject enters into the
digital interface a high count of body weight measurement
activities, the comparison engine can indicate that the subject is
likely to achieve a therapeutic milestone. As yet another example,
if a subject enters into the digital interface a low count of body
weight measurement activities, the comparison engine can indicate
that the subject is unlikely to achieve a therapeutic
milestone.
[0111] In preferred embodiments, the prediction is a function of 2,
3, 4, 5, 6, 7, 8, 9, 10, or more of a number, count, rate,
intensity, or entry activity of meal plan use; meal fallback;
activity; coaching call; shopping list use; water-intake; a number
of meal plan meals consumed, or a body weight measurement.
[0112] The method can further include 340, providing the subject
with milestone achievement input. The milestone achievement input
can be a communication (e.g., displayed by the digital interface)
that indicates likelihood of achieving the therapeutic milestone.
The milestone achievement input can be in the form of a graphical
icon or a numerical score, or a combination thereof. The milestone
achievement input can suggest additional or alternative lifestyle
interventions or regimens for increasing the likelihood or degree
of milestone achievement. In some case, the milestone achievement
input communicates a number, degree, or proportion by which the
subject, in one or more compliance parameters, has lagged prior
individuals in the database that successfully achieved the
milestone, or has lagged a population of prior individuals in the
database, which population of prior individuals is overrepresented
by milestone achievers as compared to the average individual.
[0113] For example in some embodiments, coaching call completion
shows a strong positive correlation with weight loss. In this case,
a subject who has entered a low number of completed coaching calls
via a digital interface can be predicted as unlikely to achieve the
weight loss milestone. The milestone achievement input can suggest
completing more coaching calls, or indicate the difference between
coaching calls completed by the subject and coaching calls
completed by the highest weight loss quartile of the prior
individuals in the database, or provide for and/or schedule a
follow-up meeting with one or more human service providers (e.g.,
health coach, dietician, nutritionist, chef-educator, nurse
practitioner, physical therapist, kinesiologist, physician,
behavioral psychologist, psychiatrist, and the like). Such
care-escalation protocols can include a suggestion to complete one
or more individual (one-on-one) or small-group coaching sessions
with a medical provider (e.g., nurse practitioner, physical
therapist, kinesiologist, physician, behavioral psychologist,
psychiatrist, or a combination thereof). In some cases, where a
subject enters a low number, count, rate, intensity, or entry
activity of meal plan use; meal fallback; shopping list use; or
number of meal plan meals consumed, the methods described herein
can include a suggestion to complete one or more individual
(one-on-one) or small-group coaching sessions with a health coach,
nutritionist, dietician, and/or chef-educator. In this way, more
time-consuming and/or expensive human resources and/or personal
medical care can be more efficiently implemented in escalating
fashion when needed in order to assist the subject with their
milestone achievement, and is not utilized with individuals who are
likely to reach their milestone achievement in any event.
[0114] In some embodiments the method or portions thereof is
repeated one or more times. For example, after receiving the
subject-specific data 320, the digital interface 310 can be
provided to the subject for entry into the digital interface of
subject specific data for one or more validated compliance
parameters. Additionally or alternatively, the method can be
repeated after the comparing step of 335. Additionally or
alternatively, the method can be repeated after the providing step
of 340. The repeating can be at a set frequency, such as hourly,
daily, weekly, etc. (e.g., throughout the duration of the lifestyle
intervention regimen). Alternatively, the repeating can be for a
set number of times throughout the duration of the lifestyle
intervention regimen. For example, the method can provide the
digital interface for entry of subject-specific data about 2, 3, 4,
5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or more times for the
duration of the lifestyle intervention regimen. As another example,
the repeating can be on a continual basis or initiated by the
subject's access of the digital interface on the user-local
device.
[0115] In some embodiments, a method 400 is provided, including
step 410 providing a digital interface to a subject having or at
risk of having a cardiometabolic disorder. Typically, the digital
interface is displayed on a user-local device. In some cases, the
digital interface is provided by transmitting instructions to
display the digital interface from a remote server to the
user-local device. In other cases, the instructions to display the
digital interface can be stored on the user-local device. In yet
other cases, a portion of the instructions to display the digital
interface can be stored on the user-local device, and a portion of
the instructions transmitted to the user-local device from a remote
server. The instructions can be stored and/or transmitted in the
form of transitory or non-transitory computer readable media.
[0116] The digital interface of this embodiment is configured to
receive subject-specific data for one or more validated compliance
parameters that is entered by the subject via the digital
interface. The validated compliance parameters can be validated as
associated with a therapeutic milestone for the cardiometabolic
disorder. The therapeutic milestone can be an improvement in
cardiometabolic health condition, or a target level of improvement
in a cardiometabolic health condition. In some cases, the
therapeutic milestone for the cardiometabolic disorder is selected
by the subject via the digital interface. In other cases, the
therapeutic milestone for the cardiometabolic disorder is
pre-selected by the digital interface provider or a reference
physician.
[0117] The method can further include a step 415a, in which a
subject receives from the digital interface a lifestyle
intervention regimen. Typically, the lifestyle intervention regimen
is displayed as a series of lifestyle activities (e.g., diet or
meal plans, exercise plans, hydration instructions, etc.) or
provided as a file containing the series of lifestyle
activities.
[0118] The method can further include a step 415b, in which a
subject enters subject-specific data for one or more validated
compliance parameters. Such data can include one or more of the
following: whether a meal plan was followed; whether a lifestyle
regimen activity was completed; whether a coaching call was
completed; whether one or more, or all, ingredients on a shopping
list were procured; whether the subject consumed a specified amount
of water or whether the subject consumed water; a number of meal
plan meals consumed, a number of activities completed, a total
amount of time engaged in one or more activities, a number of
coaching calls completed, length of one or more coaching calls, a
number or fraction of ingredients procured from a shopping list, a
number of hydration events, or a total volume of hydration. In some
cases, where a meal plan was not followed, the data can include
whether a meal fallback was consumed. In some cases, data can
include type, frequency and/or intensity of exercise completed
and/or logged. In some cases, data can include number or frequency
of body weight measurements performed.
[0119] In preferred embodiments, the dietary regiments employed in
the subject methods comprise, consist essentially of or consist of
a plant-based diet.
[0120] In some cases, the data can be received, stored, and/or
transmitted as a Boolean variable (e.g., true or false). For
example, meal plan use data can be stored as a true indicating a
meal plan was used (i.e., the meal specified by the meal plan was
consumed) or a false indicating that a meal plan was not used
(i.e., the meal specified by the meal plan was not consumed). In
some cases, the data can be received, stored, and/or transmitted as
a numerical variable (e.g., amount of time engaged in one or more
exercise activities, number of meals consumed, or number of
coaching calls completed).
[0121] In an optional step 415c, that may be present or absent in
this embodiment, the subject enters one or more body metric
measurements. The one or more body metric measurements can be or
include body weight, lipid profile, cholesterol level, triglyceride
levels, low-density lipoprotein level, high-density lipoprotein
level, very low-density lipoprotein level, blood pressure, fasting
blood glucose level, pre-prandial blood glucose level,
post-prandial blood glucose level, blood insulin level, blood GIP
level, insulin resistance, or glycated hemoglobin (HbA1c)
level.
[0122] The method can further include a step 420, in which the
subject-specific data entered into the digital interface by the
subject is received. In some embodiments, the subject-specific
data, or a portion thereof, is transmitted from the user-local
device and received by a remote server. In some cases, the remote
server includes a comparison engine. In some cases, the remote
server transmits the subject-specific data or a component thereof
to a comparison engine. The method can further include 435,
comparing a rate or number of the subject specific data with a
database of entry activity by prior subjects.
[0123] The comparison engine can output a milestone achievement
input such as a prediction of likelihood of achievement of the
therapeutic milestone for the cardiometabolic disorder based on the
entry activity by prior subjects. The milestone achievement input
(e.g., likelihood of achievement of therapeutic milestone) can be
determined as a function of engagement with the digital interface
(i.e., number of times a subject has entered one or more, or all,
subject-specific data), engagement with the lifestyle regimen
(i.e., rate of compliance with lifestyle regimen activities, meal
plans and the like). The milestone achievement input (e.g.,
likelihood of achievement of therapeutic milestone) can be
determined as a function of one or more compliance parameters
(e.g., true, false, number, or rate). For example, the milestone
achievement input can be determined as a function of whether a meal
plan was followed or logged; or if not, whether a meal fallback was
consumed or logged; whether a lifestyle regimen activity was
completed or logged; whether a coaching call was completed or
logged; whether ingredients on a lifestyle regimen shopping list
were procured or logged; whether the subject consumed a specified
amount of water or whether water-intake was logged; a number of
meal plan meals consumed, a number of activities completed, a total
amount of time engaged in one or more activities, a number of
coaching calls completed, length of one or more coaching calls, a
number or fraction of ingredients procured from a shopping list, a
number of hydration events, a total volume of hydration logged, or
a number or rate of body weight measurements performed. In some
cases, the milestone achievement input can be determined as a
function of type, duration, frequency and/or intensity of exercise
completed and/or logged.
[0124] For example, if a subject enters a low number of
subject-specific datapoints (e.g., either relative to other members
of the subject cohort, or relative to prior subjects in the
database, or a portion thereof) into the digital interface, the
comparison engine can indicate that the subject is unlikely to
achieve a therapeutic milestone. As another example, if a subject
enters a high number of subject-specific datapoints into the
digital interface, the comparison engine can indicate that the
subject is likely to achieve a therapeutic milestone. As another
example, if a subject enters a low number of subject-specific
datapoints, or a low number of datapoints indicating successful
completion of dietary and/or exercise activities specified in the
lifestyle intervention regimen, the comparison engine can provide a
milestone achievement input requesting or encouraging additional
entry activity and/or requesting or encouraging additional
completion and entry of activities specified in the lifestyle
intervention regimen.
[0125] As yet another example, if a subject enters into the digital
interface a high number of meal plan meals consumed, the comparison
engine can indicate that the subject is likely to achieve a
therapeutic milestone. As yet another example, if a subject enters
into the digital interface a low number of meal plan meals
consumed, the comparison engine can indicate that the subject is
unlikely to achieve a therapeutic milestone. As yet another
example, if a subject enters into the digital interface a high
number of meal fallbacks consumed, the comparison engine can
indicate that the subject is likely to achieve a therapeutic
milestone. As yet another example, if a subject enters into the
digital interface a low number of meal fallbacks consumed, the
comparison engine can indicate that the subject is unlikely to
achieve a therapeutic milestone.
[0126] As yet another example, if a subject enters into the digital
interface a high number of completed coaching calls, the comparison
engine can indicate that the subject is likely to achieve a
therapeutic milestone. As yet another example, if a subject enters
into the digital interface a low number of completed coaching
calls, the comparison engine can indicate that the subject is
unlikely to achieve a therapeutic milestone. As yet another
example, if a subject enters into the digital interface a high
number of completed activities, the comparison engine can indicate
that the subject is likely to achieve a therapeutic milestone. As
yet another example, if a subject enters into the digital interface
a low number of completed activities, the comparison engine can
indicate that the subject is unlikely to achieve a therapeutic
milestone.
[0127] As yet another example, if a subject enters into the digital
interface a high number of meal water-intake events, the comparison
engine can indicate that the subject is likely to achieve a
therapeutic milestone. As yet another example, if a subject enters
into the digital interface a low number of water-intake events, the
comparison engine can indicate that the subject is unlikely to
achieve a therapeutic milestone. As yet another example, if a
subject enters into the digital interface a high volume of water
intake, the comparison engine can indicate that the subject is
likely to achieve a therapeutic milestone. As yet another example,
if a subject enters into the digital interface a low volume of
water-intake, the comparison engine can indicate that the subject
is unlikely to achieve a therapeutic milestone.
[0128] As yet another example, if a subject enters into the digital
interface a high number of shopping list ingredients procured, the
comparison engine can indicate that the subject is likely to
achieve a therapeutic milestone. As yet another example, if a
subject enters into the digital interface a low number of number of
shopping list ingredients procured, the comparison engine can
indicate that the subject is unlikely to achieve a therapeutic
milestone. As yet another example, if a subject enters into the
digital interface a high count of body weight measurement
activities, the comparison engine can indicate that the subject is
likely to achieve a therapeutic milestone. As yet another example,
if a subject enters into the digital interface a low count of body
weight measurement activities, the comparison engine can indicate
that the subject is unlikely to achieve a therapeutic
milestone.
[0129] In preferred embodiments, the prediction is a function of 2,
3, 4, 5, 6, 7, 8, 9, 10, or more of a number, count, rate,
intensity, or entry activity of meal plan use; meal fallback;
activity; coaching call; shopping list use; water-intake; a number
of meal plan meals consumed, or a body weight measurement.
[0130] The method can further include 440, providing the subject
with milestone achievement input. The milestone achievement input
can be a communication (e.g., displayed by the digital interface)
that indicates likelihood of achieving the therapeutic milestone.
The milestone achievement input can be in the form of a graphical
icon or a numerical score, or a combination thereof. The milestone
achievement input can suggest additional or alternative lifestyle
interventions or regimens for increasing the likelihood or degree
of milestone achievement. In some case, the milestone achievement
input communicates a number, degree, or proportion by which the
subject, in one or more compliance parameters, has lagged prior
individuals in the database that successfully achieved the
milestone, or has lagged a population of prior individuals in the
database, which population of prior individuals is overrepresented
by milestone achievers as compared to the average individual.
[0131] For example in some embodiments, coaching call completion
shows a strong positive correlation with weight loss. In this case,
a subject who has entered a low number of completed coaching calls
via a digital interface can be predicted as unlikely to achieve the
weight loss milestone. The milestone achievement input can suggest
completing more coaching calls, or indicate the difference between
coaching calls completed by the subject and coaching calls
completed by the highest weight loss quartile of the prior
individuals in the database, or provide for and/or schedule a
follow-up meeting with one or more human service providers (e.g.,
health coach, dietician, nutritionist, chef-educator, nurse
practitioner, physical therapist, kinesiologist, physician,
behavioral psychologist, psychiatrist, and the like). Such
care-escalation protocols can include a suggestion to complete one
or more individual (one-on-one) or small-group coaching sessions
with a medical provider (e.g., nurse practitioner, physical
therapist, kinesiologist, physician, behavioral psychologist,
psychiatrist, or a combination thereof). In some cases, where a
subject enters a low number, count, rate, intensity, or entry
activity of meal plan use; meal fallback; shopping list use; or
number of meal plan meals consumed, the methods described herein
can include a suggestion to complete one or more individual
(one-on-one) or small-group coaching sessions with a health coach,
nutritionist, dietician, and/or chef-educator.
[0132] In some embodiments of the method or portions thereof, is
repeated one or more times. For example, after receiving the
subject-specific data 420, the digital interface 410 can be
provided to the subject for entry into the digital interface of
subject specific data for one or more validated compliance
parameters. Additionally or alternatively, the method can be
repeated after the comparing step of 435. Additionally or
alternatively, the method can be repeated after the providing step
of 440. The repeating can be at a set frequency, such as hourly,
daily, weekly, etc. (e.g., throughout the duration of the lifestyle
intervention regimen). Alternatively, the repeating can be for a
set number of times throughout the duration of the lifestyle
intervention regimen. For example, the method can provide the
digital interface for entry of subject-specific data about 2, 3, 4,
5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or more times for the
duration of the lifestyle intervention regimen. As another example,
the repeating can be on a continual basis or initiated by the
subject's access of the digital interface on the user-local
device.
[0133] Cardiovascular Disease
[0134] Cardiovascular disease is the major cause of morbidity and
mortality in the Western world (Brunzell et al. Lipoprotein
Management in Patients with Cardiometabolic Risk, Diabetes Care
2008 31: 811-822), and the initial presentation of coronary
arterial disease in particular manifests as sudden death in up to
one-third of patients. Id. To more effectively address this rapidly
growing public health problem the American Diabetes Association and
the American College of Cardiology Foundation have also jointly
developed and advocated for the treatment of cardiometabolic risk
(CMR), which refers to a high lifetime risk of CVD. (Eckel et al.
Preventing Cardiovascular Disease and Diabetes, Diabetes Care 2006
29:1697-1699). Notably, the risk factors for cardiovascular disease
and type 2 diabetes often cluster, including obesity, insulin
resistance, hyperglycemia, dyslipoproteinemia and hypertension. As
such, a patient having or at risk of having a "cardiometabolic
disorder" as described herein refers to a patient having one or
more of these risk factors, e.g. including cardiovascular disease
(stroke, heart failure, coronary artery disease and myocardial
infarction), diabetes, and metabolic syndrome.
[0135] The term "cardiovascular disease" herein refers to any
disease or disorder of the heart or blood vessels (i.e. arteries
and veins) or any symptom thereof, or any disease or condition that
causes or contributes to a cardiovascular disease." Non-limiting
examples of cardiovascular diseases include acute cardiac ischemic
events, acute myocardial infarction, angina, angina pectoris,
arrhythmia, atrial fibrillation, atherosclerosis, arterial
fibrillation, cardiac insufficiency, cardiovascular disease,
chronic heart failure, chronic stable angina, congestive heart
failure, coronary artery disease, coronary heart disease, deep vein
thrombosis, diabetes, diabetes mellitus, diabetic neuropathy,
diastolic dysfunction in subjects with diabetes mellitus, edema,
essential hypertension, eventual pulmonary embolism, fatty liver
disease, heart disease, heart failure, homozygous familial
hypercholesterolemia (HoFH), homozygous familial sitosterolemia,
hypercholesterolemia, hyperlipidemia, hyperlipidemia in HIV
positive subjects, hypertension, hypertriglyceridemia, ischemic
complications in unstable angina and myocardial infarction, low
blood pressure, metabolic syndrome, mixed dyslipidemia, moderate to
mild heart failure, myocardial infarction, obesity management,
paroxysmal atrial/arterial fibrillation/fibrulation/flutter,
paroxysmal supraventricular tachycardias (PSVT), particularly
severe or rapid onset edema, platelet aggregation, primary
hypercholesterolemia, primary hyperlipidemia, pulmonary arterial
hypertension, pulmonary hypertension, recurrent hemodynamically
unstable ventricular tachycardia (VT), recurrent ventricular
arrhythmias, recurrent ventricular fibrillation (VF), ruptured
aneurysm, sitisterolemia, stroke, supraventricular tachycardia,
symptomatic atrial fibrillation/flutter, tachycardia, type-II
diabetes, vascular disease, venous thromboembolism, ventricular
arrhythmias, and other cardiovascular events.
[0136] Metabolic Disorders
[0137] The compositions and methods of the present invention also
find advantageous use in the treatment and/or prophylaxis of a wide
variety of clinical metabolic disorders, including obesity,
prediabetes, Polycystic Ovary Syndrome, dislipidemia or disorders
of lipid metabolism, as well as hyperglycemic conditions, such as
insulin-dependent (type 1) or -independent (type 2) diabetes, as
well as physiological conditions or disorders associated with or
that result from the hyperglycemic condition. Thus, hyperglycemic
conditions treatable by a method of the invention also include a
histopathological change associated with chronic or acute
hyperglycemia (e.g., diabetes). Particular examples include
degeneration of pancreas (13-cell destruction), kidney tubule
calcification, degeneration of liver, eye damage (diabetic
retinopathy), diabetic foot, ulcerations in mucosa such as mouth
and gums, excess bleeding, delayed blood coagulation or wound
healing and increased risk of coronary heart disease, stroke,
peripheral vascular disease, dyslipidemia, hypertension and
obesity.
[0138] As used herein, the term "hyperglycemic" or "hyperglycemia,"
when used in reference to a condition of a patient, means a
transient or chronic abnormally high level of glucose present in
the blood of a patient. The condition can be caused by a delay in
glucose metabolism or absorption such that the patient exhibits
glucose intolerance or a state of elevated glucose not typically
found in normal patients (e.g., in glucose-intolerant subdiabetic
patients at risk of developing diabetes, or in diabetic patients).
Fasting plasma glucose (FPG) levels for normoglycemia are less than
about 100 mg/dl, for impaired glucose metabolism, between about 110
and 126 mg/dl, and for diabetics greater than about 126 mg/dl.
[0139] Metabolic disorders also include obesity or an undesirable
body mass. Leptin, cholecystokinin, PYY and GLP-1 decrease hunger,
increase energy expenditure, induce weight loss or provide normal
glucose homeostasis. Disorders treatable also include those
typically associated with obesity, for example, abnormally elevated
serum/plasma LDL, VLDL, triglycerides, cholesterol, plaque
formation leading to narrowing or blockage of blood vessels,
increased risk of hypertension/stroke, coronary heart disease,
etc.
[0140] The effect of improving a lifestyle-related health condition
of a subject using one or more of the methods or systems described
herein on aspects of diabetic disease can be evaluated according to
methods known in the art and common practiced by physicians
treating diabetic subjects.
[0141] Efficacy of treatment of diabetes/metabolic syndrome and
diabetes-associated conditions with the compositions and methods
described herein can be assessed using assays and methodologies
known in the art. By way of example, quantitative assessment of
renal function and parameters of renal dysfunction are well known
in the art. Examples of assays for the determination of renal
function/dysfunction include serum creatinine level; creatinine
clearance rate; cystatin C clearance rate, 24-hour urinary
creatinine clearance, 24-hour urinary protein secretion; Glomerular
filtration rate (GFR); urinary albumin creatinine ratio (ACR);
albumin excretion rate (AER); and renal biopsy.
[0142] Quantitative assessment of pancreatic function and
parameters of pancreatic dysfunction or insufficiency are also well
known in the art. Examples of assays for the determination of
pancreas function/dysfunction include evaluating pancreatic
functions using biological and/or physiological parameters such as
assessment of islets of Langerhans size, growth and/or secreting
activity, beta-cells size, growth and/or secreting activity,
insulin secretion and circulating blood levels, glucose blood
levels, imaging of the pancreas, and pancreas biopsy, glucose
uptake studies by oral glucose challenge, assessment of cytokine
profiles, blood-gas analysis, extent of blood-perfusion of tissues,
and angiogenesis within tissues.
[0143] Additional assays for treatment of diabetes and
diabetes-associated conditions are known in the art and are
contemplated herein.
[0144] Hormone Modulation
[0145] The lifestyle intervention regimen also modulates hormone
concentrations and/or concentrations of hormones including, but not
limited to, GLP-1, GLP-2, GIP, oxyntomodulin, PYY, CCK, glycentin,
insulin, glucagon, ghrelin, amylin, C-peptide and uroguanylin.
Sampling of hormones can be performed frequently during or after
the lifestyle intervention regimen and/or participating in one or
more of the methods described herein. Subjects can be undergoing or
not undergoing treatment to cause systemic inhibition of
dipeptidyl-peptidase IV (DPP-IV) to augment the circulating
half-life of the relevant hormones that can be degraded by
DPP-IV.
[0146] In some embodiments, improving a lifestyle-related health
condition of a subject using one or more of the methods or systems
described herein modulates GLP-1. In some embodiments, improving a
lifestyle-related health condition of a subject using one or more
of the methods or systems described herein modulates GLP-2. In some
embodiments, improving a lifestyle-related health condition of a
subject using one or more of the methods or systems described
herein modulates GIP.
[0147] In some embodiments, improving a lifestyle-related health
condition of a subject using one or more of the methods or systems
described herein modulates oxyntomodulin. In some embodiments,
improving a lifestyle-related health condition of a subject using
one or more of the methods or systems described herein modulates
PYY. In some embodiments, improving a lifestyle-related health
condition of a subject using one or more of the methods or systems
described herein CCK. In some embodiments, improving a
lifestyle-related health condition of a subject using one or more
of the methods or systems described herein modulates glycentin.
[0148] In some embodiments, improving a lifestyle-related health
condition of a subject using one or more of the methods or systems
described herein modulates insulin. In some embodiments, improving
a lifestyle-related health condition of a subject using one or more
of the methods or systems described herein modulates glucagon. In
some embodiments, improving a lifestyle-related health condition of
a subject using one or more of the methods or systems described
herein modulates, ghrelin.
[0149] In some embodiments, improving a lifestyle-related health
condition of a subject using one or more of the methods or systems
described herein modulates amylin. In some embodiments, improving a
lifestyle-related health condition of a subject using one or more
of the methods or systems described herein modulates C-peptide. In
some embodiments, improving a lifestyle-related health condition of
a subject using one or more of the methods or systems described
herein modulates uroguanylin.
[0150] In embodiments, the levels of hormones assayed in
association with the methods of the invention, including, but not
limited to, GLP-1, GLP-2, GIP, oxyntomodulin, PYY, CCK, glycentin,
insulin, glucagon, ghrelin, amylin, uroguanylin, C-peptide and/or
combinations thereof are detected according to standard methods
described in the literature. For example, proteins can be measured
by immunological assays, and transcription products by nucleic acid
amplification techniques. Functional assays described in the art
can also be used as appropriate. In embodiments, samples assayed
comprise cultured cells, patient cell or tissue samples, patient
body fluids, e.g., blood or plasma, etc. Similarly, the levels of
analytes (e.g., glucose, triglycerides, HDL, LDL, apoB and the
like) assayed in association with the methods of the invention are
detected according to any known method.
[0151] In some embodiments, patients are pre-evaluated for
expression of metabolic hormones using methods described herein.
The therapy provided to the individual can thus be targeted to his
or her specific needs. In embodiments, a patient's hormonal profile
is pre-evaluated and depending on the changes that the physician
desires to affect, a certain lifestyle intervention regimen is
administered. The evaluation process can be repeated and the
treatment adjusted accordingly at any time during or following
treatment.
[0152] Reducing Pharmaceutical Interventions
[0153] In some embodiments, the methods, systems, and computer
program products described herein can achieve a therapeutic
milestone in a subject having a cardiometabolic disorder or at risk
of having a cardiometabolic disorder without pharmaceutical
intervention or with a reduced dosing (e.g., dose amount and/or
dose frequency) of one or more pharmaceutical interventions. For
example, in a patient having or at risk of having type-II diabetes,
a relevant therapeutic milestone can comprise, e.g., maintenance of
HbA1c, fasting glucose, fasting insulin, alanine transaminase,
and/or fasting lipids, and/or any other therapeutic milestone
markers described herein relevant to evaluating diabetes treatment
such as a hormone level, renal function biomarker, and the like, at
a level indicative of a therapeutic benefit. In some cases, a
patient having or at risk of having type-II diabetes can achieve
one or more of the therapeutic milestones for type-II diabetes
without pharmaceutical intervention or with a reduced dosing (e.g.,
dose amount and/or dose frequency) of one or more of biguanides;
sulfonylureas; meglitinide derivatives; alpha-glucosidase
inhibitors; thiazolidinediones (TZDs); glucagonlike peptide-1
(GLP-1) agonists; dipeptidyl peptidase IV (DPP-4) inhibitors;
selective sodium-glucose transporter-2 (SGLT-2) inhibitors, and
insulin.
[0154] As another example, in a patient having or at risk of heart
disease, a relevant therapeutic milestone can comprise, e.g.,
weight loss, improved lipid profile, lower blood pressure, and/or
lower resting pulse rate, or any other therapeutic milestone
described herein relevant to evaluating treatment of heart disease.
In some cases, a patient having or at risk of having heart disease
can achieve one or more of the therapeutic milestones for heart
disease without pharmaceutical intervention or with a reduced
dosing (e.g., dose amount and/or dose frequency) of a beta-blocking
agent, an alpha-blocking agent, an angiotensin-converting enzyme
inhibitor, a statin, a diuretic, and a calcium channel blocker.
[0155] As another example, in a patient having or at risk of
hypertension, a relevant therapeutic milestone can comprise, e.g.,
maintenance of a diastolic and/or systolic blood pressure, or any
other therapeutic milestone described herein relevant to evaluating
treatment of hypertension, at a level indicative of therapeutic
benefit. In some cases, a patient having or at risk of hypertension
can achieve one or more of the therapeutic milestones for
hypertension without pharmaceutical intervention or with a reduced
dosing (e.g., dose amount and/or dose frequency) of a beta-blocking
agent, an alpha-blocking agent, an angiotensin-converting enzyme
inhibitor, an angiotensin II receptor blocker, a calcium channel
blocker, a diuretic, and a renin inhibitor.
[0156] As another example, in a patient having or at risk of
hyperlipidemia, a relevant therapeutic milestone can comprise,
e.g., maintenance of a diastolic and/or systolic blood pressure, or
any other therapeutic milestone described herein relevant to
evaluating treatment of hyperlipidemia, at a level indicative of
therapeutic benefit. In some cases, a patient having or at risk of
hyperlipidemia can achieve one or more of the therapeutic
milestones for hyperlipidemia without pharmaceutical intervention
or with a reduced dosing (e.g., dose amount and/or dose frequency)
of a statin, exetimibe, and PCSK9 inhibitors statin.
[0157] As another example, in a patient having or at risk of
coronary artery disease, a relevant therapeutic milestone can
comprise, e.g., maintenance of a diastolic and/or systolic blood
pressure, or any other therapeutic milestone described herein
relevant to evaluating treatment of coronary artery disease, at a
level indicative of therapeutic benefit. In some cases, a patient
having or at risk of coronary artery disease can achieve one or
more of the therapeutic milestones for hyperlipidemia without
pharmaceutical intervention or with a reduced dosing (e.g., dose
amount and/or dose frequency) of a) a cholesterol-modifying
medication selected from the group consisting of a statin,
exetimibe, and PCSK9 inhibitors; b) an anti-coagulant, preferably
selected from the group consisting of an anti-platelet agent (e.g.
aspirin or Plavix), warfarin, low-molecular weight heparin, a
direct thrombin inhibitor, and a factor Xa inhibitor; c) a
beta-blocking agent, d) a vasodilator; e) a diuretic; and f) an
angiotensin-converting enzyme inhibitor and an angiotensin II
receptor blocking agent.
[0158] Biguanides contemplated for reduction in accordance with the
subject invention include, e.g. metformin, phenformin, buformin and
like compounds described herein. Statins or HMG-CoA reductase
inhibitors contemplated for reduction in accordance with the
subject invention include, e.g. lovastatin, atorvastatin,
fluvastatin, rosuvastatin, simvastatin, pravastatin, pitavastatin,
and the like. Additional active agents contemplated for reduction
in accordance with the subject compositions and methods include,
e.g. anti-hypertensives and anti-platelet agents as well as
diuretics, bile acid sequesterants, incretin enhancers and
mimetics, oral anti-diabetic agents, anti-obesity agents, and
anti-atherosclerotics.
[0159] Anti-hypertensives contemplated for reduction in accordance
with the subject invention include, e.g., beta blockers (atenolol,
betaxolol, metoprolol, nadolol, nebivolol, oxprenolol, pindolol,
propranolol, timolol, etc.), alpha-1 blockers (alfuzosin,
arotinolol, doxazosin, indoramin, moxisylyte, phenoxybenzamine,
phentolamine, prazosin, silodosin, tamsulosin, terazosin,
tolazoline, trimazosin), alpha-2 agonists (apraclonidine,
brimonidine, clonidine, guanabenz, guanfacine, lofexidine,
tolonidine, mixed alpha/beta blockers (bucindolol, carvedilol,
labetalol, etc.), calcium channel blockers such as dihydropyridines
(amlodipine, felodipine, isradipine, lercanidipine, nicardipine,
nifedipine, nimodipine, nitrendipine, etc.) and
non-dihydropyridines (diltiazem, verapamil, etc.), renin inhibitors
(aliskiren), ACE inhibitors (captopril, enalapril, fosinopril,
lisinopril, perindopril, quinapril, ramipril, trandolapril,
benazepril, etc.), angiotensin II receptor antagonists
(candesartan, eprosartan, irbesartan, losartan, olmesartan,
telmisartan, valsartan, etc.), and the like.
[0160] Anti-platelet medications contemplated for reduction in
accordance with the subject invention include, e.g., cyclooxygenase
inhibitors (acetylsalicylic acid (aspirin), aloxiprin, carbasalate
calcium, indobufen, trifusal, etc.), ADP receptor inhibitors
(clopidogrel, ticlopidine, ticagrelor, etc.), phosphodiesterase
inhibitors (cilostazol, etc.), adenose reuptake inhibitors
(dipyridamole, etc.), thromboxane synthase or receptor inhibitors
(picotamide, ramatroban, terbogrel, etc.), anagrelide, prasugrel,
cloricromen, and the like.
[0161] Diuretics contemplated for reduction in accordance with the
subject invention include e.g., loop diuretics (bumetanide,
ethacrynic acid, furosemide, torsemide, etc.), thiazide diuretics
(epitizide, hydrochlorothiazide, chlorothiazide,
bendroflumethiazide, etc.), thiazide-like diuretics (indapamide,
chlorthalidone, metolazone, etc.), potassium-sparing diuretics
(amiloride, triamterene, spironolactone, etc.), and the like.
[0162] Bile acid sequesterants contemplated for reduction in
accordance with the subject invention include, e.g.,
cholestyramine, colesevelam, colestipol, and the like.
[0163] Suitable incretin mimetics and enhancers for use in the
subject invention include, e.g., peptidic and non-peptidic GLP-1
mimetics (including, e.g., allosteric activators of the GLP-1
receptor), peptidic and non-peptidic PYY mimetics, peptidic and
non-peptidic Ghrelin antagonists and the like.
[0164] Suitable oral anti-diabetic agents for use in combination
with metformin in the subject compositions and methods include,
e.g., sulfonylureas (glyburide, glimepiride, glipizide, gliclazide,
glycopyramide, gliquidone, tolbutamide, acetohexamide, tolazamide,
chlorpropamide, carbutamide, etc.), nonsulfonylureas (repaglinide,
nateglinide, etc.), thiazolidinediones (rosiglitazone,
pioglitazone, rivoglitazone, troglitazone, ciglitazone,
darglitazone, netoglitazone, englitazone, etc.), dual PPAR agonists
(e.g., aleglitazar, farglitazar, muraglitazar, tesaglitazar,
telmisartan, and the like), dipeptidyl peptidase-4 inhibitors
(vildagliptin, sitagliptin, saxagliptin, linagliptin, allogliptin,
septagliptin, berberine, etc.), sodium-glucose co-transporter-1 or
2 (SGLT1 or 2) inhibitors (canagliflozin, empagliflozin,
dapagliflozin, LX4211, etc.) meglitinides (nateglinide,
repaglinide, etc.), alpha-glucosidase inhibitors (acarbose,
miglitol, voglibose, etc.), agonists of GPR40, GPR120, GPR119,
GPR41, GPR43, and the like.
[0165] Suitable anti-obesity agents for use for use in the subject
invention include, e.g., Orlistat (Zenical), Lorcaserin (Belviq),
Sibutramine (Meridia, withdrawn from most markets), Rimonabant
(Acomplia), Exenatide (Byetta and Bydureon), Pramlintide (Symlin),
Redux, ZGN-433, Phentermine/topiramate (Qsymia),
Naltrexone/buproprion (Contrave), as well as alternative medicine
options including, e.g., conjugated linoleic acid, green tea
extract, khat, lipoic acid, ECA Stack (Ephedrine Caffeine Stack),
Raspberry ketone and the like.
[0166] Suitable anti-artherosclerotics for use in the subject
invention include compounds that can reduce atherosclerosis
independent of changes in other risk factors, e.g. fish oil as well
as inhibitors of proprotein convertase subtilisin/kexin type 9
(PCSK9) such as AMG145 (Amgen), 1D05-IgG2 (Merck & Co.), and
SAR236553/REGN727 (Aventis/Regeneron), peptides mimicking the LDLR
that binds to PCSK9 (e.g. Shan et al. (2008) Biochem. Biophys. Res.
Commun. 375: 69-73), and nucleic acid therapeutics targeting PCSK9
(e.g Graham et al. (2007) J. Lipid Res. 48:763-7; Lindholm et al.
(2012) Mol. Ther. 20:376-81).
[0167] Also contemplated as additional active agents are HDL/LDL
ratio modifying compounds including, e.g., niacin, acipomox,
MK-0354, other modulators of GPR81, GPR109A, GPR109B and the
like.
Definitions
[0168] "Treating" or "treatment" of any condition, disease or
disorder refers, in some embodiments, to ameliorating the disease
or disorder (i.e., arresting or reducing the development of the
disease or at least one of the clinical symptoms thereof). In other
embodiments "treating" or "treatment" refers to ameliorating at
least one physical parameter, which may not be discernible by the
patient. In yet other embodiments, "treating" or "treatment" refers
to inhibiting the disease or disorder, either physically, (e.g.,
stabilization of a discernible symptom), physiologically, (e.g.,
stabilization of a physical parameter) or both. In yet other
embodiments, "treating" or "treatment" refers preventing or to
delaying the onset of the disease or disorder.
[0169] "Therapeutically effective amount" or "effective amount"
means the amount of a composition, compound, therapy, or course of
treatment that, when administered to an individual for treating a
disorder or disease, is sufficient to effect such treatment for the
disorder or disease. The "therapeutically effective amount" will
vary depending on the composition, the compound, the therapy, the
course of treatment, the disorder or disease and its severity and
the age, weight, etc., of the individual to be treated.
[0170] Systems
[0171] Aspects of the invention described herein can be performed
using any type of computing device, such as a computer, that
includes a processor, e.g., a central processing unit, or any
combination of computing devices where each device performs at
least part of the process or method. In some embodiments, systems
and methods described herein may be performed with a handheld
device, e.g., a smart tablet, smart watch or a smart phone, or a
specialty device produced for the system.
[0172] Methods of the invention can be performed using software,
hardware, firmware, hardwiring, or combinations of any of these.
Features implementing functions can also be physically located at
various positions, including being distributed such that portions
of functions are implemented at different physical locations (e.g.,
digital interface in one location, computer server for providing
said digital interface to user local device and/or receiving
subject-specific data, and computer for hosting the database of
entry activity by prior subjects in another location, e.g., in
separate buildings, for example, with wireless or wired
connections). In some cases, one or more functions are in the same
location or on the same computer. For example, the function of
hosting the database and comparing rate or number of
subject-specific data with the database of entry activity by prior
subjects can be performed on the same device, or a different
device.
[0173] Processors suitable for the execution of computer programs
include, by way of example, both general and special purpose
microprocessors, and any one or more processor of any kind of
digital computer. Generally, a processor will receive instructions
and data from a read-only memory or a random access memory or both.
The essential elements of a computer are a processor for executing
instructions and one or more memory devices for storing
instructions and data. Generally, a computer will also include, or
be operatively coupled to receive data from or transfer data to, or
both, one or more mass storage devices for storing data, e.g.,
magnetic, magneto-optical disks, or optical disks. Information
carriers suitable for embodying computer program instructions and
data include all forms of non-volatile memory, including, by way of
example, semiconductor memory devices, (e.g., EPROM, EEPROM, solid
state drive (SSD), and flash memory devices); magnetic disks,
(e.g., internal hard disks or removable disks); magneto-optical
disks; and optical disks (e.g., CD and DVD disks). The processor
and the memory can be supplemented by, or incorporated in, special
purpose logic circuitry.
[0174] To provide for interaction with a user, the subject matter
described herein can be implemented on a computer having an I/O
device, e.g., a CRT, LCD, LED, or projection device for displaying
information to the user (e.g., the digital interface and/or the
milestone achievement input) and an input or output device such as
a keyboard and a pointing device, (e.g., a mouse or a trackball),
by which the user can provide input to the computer. Other kinds of
devices can be used to provide for interaction with a user as well,
and input from the user can be received in any form, including
acoustic, speech, or tactile input.
[0175] The subject matter described herein can be implemented in a
computing system that includes a back-end component (e.g., a data
server), a middleware component (e.g., an application server), or a
front-end component (e.g., a client computer having a graphical
user interface or a web browser through which a user can interact
with an implementation of the subject matter described herein), or
any combination of such back-end, middleware, and front-end
components. The components of a system can be interconnected
through a network by any form or medium of digital data
communication, e.g., a communication network. For example, a
reference set of data (e.g., the database of entry activity by
prior subjects) may be stored at a remote location and a computer
can communicate across a network to access the reference set for
purposes of comparing data. In other embodiments, however, a
reference set is stored locally within the computer and the
computer accesses the reference set within the CPU for purposes of
comparing data. Examples of communication networks include cell
network (e.g., 3G or 4G), a local area network (LAN), and a wide
area network (WAN), e.g., the Internet.
[0176] The subject matter described herein can be implemented as
one or more computer program products, such as one or more computer
programs tangibly embodied in an information carrier (e.g., in a
non-transitory computer-readable medium) for execution by, or to
control the operation of, data processing apparatus (e.g., a
programmable processor, a computer, or multiple computers) to
perform one or more of the methods described herein. A computer
program (also known as a program, software, software application,
app, macro, or code) can be written in any form of programming
language, including compiled or interpreted languages (e.g., C,
C++, Perl), and it can be deployed in any form, including as a
stand-alone program or as a module, component, subroutine, or other
unit suitable for use in a computing environment. Systems and
methods of the invention can include instructions written in any
suitable programming language known in the art.
[0177] A computer program does not necessarily correspond to a
file. A program can be transitory or non-transitory medium that is
stored in a file or a portion of a file that holds other programs
or data, in a single file dedicated to the program in question, or
in multiple coordinated files (e.g., files that store one or more
modules, sub-programs, or portions of code). A computer program can
be deployed to be executed on one computer or on multiple computers
at one site or distributed across multiple sites and interconnected
by a communication network.
[0178] A file can be a digital file, for example, stored on a hard
drive, SSD, CD, or other tangible, non-transitory medium. A file
can be sent from one device to another over a network (e.g., as
packets being sent from a server to a client, for example, through
a Network Interface Card, modem, wireless card, or similar).
[0179] Writing a file according to the invention involves
transforming a tangible, non-transitory computer-readable medium,
for example, by adding, removing, or rearranging particles (e.g.,
with a net charge or dipole moment into patterns of magnetization
by read/write heads), the patterns then representing new
collocations of information about objective physical phenomena
desired by, and useful to, the user. In some embodiments, writing
involves a physical transformation of material in tangible,
non-transitory computer readable media (e.g., with certain optical
properties so that optical read/write devices can then read the new
and useful collocation of information, e.g., burning a CD-ROM). In
some embodiments, writing a file includes transforming a physical
flash memory apparatus such as NAND flash memory device and storing
information by transforming physical elements in an array of memory
cells made from floating-gate transistors. Methods of writing a
file are well-known in the art and, for example, can be invoked
manually or automatically by a program or by a save command from
software or a write command from a programming language.
[0180] Suitable computing devices typically include mass memory, at
least one graphical user interface, at least one display device,
and typically include communication between devices. The mass
memory illustrates a type of computer-readable media, namely
computer storage media. Computer storage media may include
volatile, nonvolatile, removable, and non-removable media
implemented in any method or technology for storage of information,
such as computer readable instructions, data structures, program
modules, or other data. Examples of computer storage media include
RAM, ROM, EEPROM, flash memory, or other memory technology, CD-ROM,
digital versatile disks (DVD) or other optical storage, magnetic
cassettes, magnetic tape, magnetic disk storage or other magnetic
storage devices, Radiofrequency Identification tags or chips, or
any other medium which can be used to store the desired information
and which can be accessed by a computing device.
[0181] Functions described above can be implemented using software,
hardware, firmware, hardwiring, or combinations of any of these.
Any of the software can be physically located at various positions,
including being distributed such that portions of the functions are
implemented at different physical locations.
[0182] As one skilled in the art would recognize as necessary or
best-suited for performance of the methods of the invention, a
computer system for implementing some or all of the described
inventive methods can include one or more processors (e.g., a
central processing unit (CPU) a graphics processing unit (GPU), or
both), main memory and static memory, which communicate with each
other via a bus.
EXAMPLES
Example 1
[0183] Participants were recruited for a 16-week pilot program. We
preferentially screened-in 601 participants to include women, in
any US state, aged 45-54, with a BMI of 30-35 kg/m.sup.2 (i.e.
Class 1 Obesity), who also reported a willingness to prepare meals
at home and eat mostly whole, plant-based foods. Ninety-five
participants started the program and 71 (74.7%) completed the 16
weeks, with an average loss of body weight of 5.1% among all
completers, and, in the top tertile of engagers (i.e. those who
made the most use of the digital tools), we found an average of
7.1% weight loss in just over 14 weeks.
[0184] Certain participants having baseline metabolic abnormalities
(i.e. elevated fasting glucose, fasting insulin, hemoglobin A1c,
alanine transaminase (ALT), and/or fasting lipids) provided before
and after program blood tests, allowing direct evaluation of
clinical responses after their participation in the 16 week
program. Among 7 participants with impaired glycemic responses at
baseline, all 7 showed improvement in A1c (5 participants improved,
with 3 of the 5 returning to normal) or insulin sensitivity (7
participants) at 16 weeks. Glycemic measures assessed include
fasting blood glucose and insulin, hemoglobin A1c, and calculated
HOMA2 (homeostatic model assessment-2) measures of beta-cell
function and insulin resistance.
Example 2
[0185] In this study, we sought to understand to what degree a
novel, skill-focused, digital therapeutic could change Hemoglobin
A1c and anti-diabetic medication use in a geographically widely
distributed sample of adults with type 2 diabetes. While the
ultimate goal of the intervention is to be more cost-effective than
other interventions, this study examines effectiveness alone.
[0186] Methods
[0187] Trial Design & Participants
[0188] We conducted a 12-week, non-blinded, single-arm
interventional study in a convenience sample of adults with a
self-reported diagnosis of Type 2 diabetes, targeting adults in any
US state with an interest in type 2 diabetes. Eligibility criteria
included having a diagnosis of type 2 diabetes, age 18 or older,
and possession of an Android or iPhone Smartphone, as demonstrated
by the ability to download the intervention app. Type 2 diabetes
status was presumed by the combination of a self-reported diagnosis
and an initial Hemoglobin A1c of 6.5% or higher. Participants were
excluded if they were not able to comply with the study protocol,
for example if they could not speak or read English or did not have
sufficient computer literacy to operate the app successfully.
[0189] Enrollment was on a first-come-first-served basis and all
data collection occurred online via electronic survey or directly
through the app. Participants who were interested in the study were
invited to download the app and enter a code to unlock the app.
Participants were then instructed by the app to create an account
using their email address. Upon creating an account, participants
were emailed an informed consent document to review. Informed
consent was obtained for each study participant via discussion with
a study staff member prior to commencing their first coaching call.
This phone call with study staff also ensured that each participant
was unique.
[0190] Intervention
[0191] The digital therapeutic consisted of use of the intervention
app paired with specialized human support, also delivered
digitally. The content design of both app and human support
incorporated evidenced-based dietary and lifestyle recommendations
such as a dietary pattern consisting mainly of whole food
plant-based meals and regular exercise meeting or exceeding
national guidelines. Ley et al., The Lancet 383:1999-2007 (2014).
Since increased meals prepared at home is associated with decreased
disease burden, Zong et al. PLOS Med 13(7):e1002052 (2016),
additional content was also developed with expert input to enhance
culinary knowledge and skill acquisition with the aim of increasing
meals prepared at home.
[0192] The app was designed to be used ad libitum, however
expectations of use were established during the informed consent
process as follows: 1. Use of the meal planning feature that
facilitates advanced planning of meals and automated shopping lists
(approximately 5 minutes per week). The meal planning feature used
default recipes that met pre-specified criteria for
ease-of-preparation, inclusion of easy-to-access, whole-food,
plant-based ingredients, and staged introduction of culinary
techniques. Participants could easily swap meals or plan to eat a
meal not in the recipe database. 2. Self-monitoring of weight daily
(via digitally connected scale provided free to participants or by
self-report in app) and the option of reporting meals made
(approximately 1-2 minutes per day). 3. Reviewing of educational
materials aimed at advancing culinary or health literacy
(approximately 15-20 minutes per week). 4. An optional, private
Facebook community was created to provide additional peer-to-peer
and expert-to-peer support (ad libitum). The app also delivered
reminders, for example to schedule a coaching call or report meals
made or eaten, in the form of in-app notifications and an ability
to message their health coach.
[0193] The primary form of human support was delivered by 30-minute
telephonic health coaching calls, scheduled at the participant's
convenience every two weeks via the study app. Health coaching is
an evidence-based practice grounded in behavior change theory that
utilizes guided conversational techniques such as motivational
interviewing. Wolever et al., Glob Adv Health Med 2(4):38-57
(2013). All study health coaches had completed training from
accredited health coaching institutions and received additional
training in lifestyle and culinary medicine, research methods, as
well as training for coaching within a clinical team prior to the
start of the study.
[0194] During the intervention period, the health coaches were
supported by a specialized team of lifestyle medicine experts
including a nurse practitioner, internist, psychiatrist,
chef-educator, and registered dietitian, who were also available to
speak to members on an as-needed basis via a care-escalation
process. Participants were asked to continue managing all
medications with their Primary Care Team or Endocrinologist during
the course of the study.
[0195] Measures
[0196] Demographics
[0197] Participants reported age, gender, height, weight and US
state of residence as a part of the signup process for the study
app.
[0198] Hemoglobin A1c and Medication Use
[0199] Most recent Hemoglobin A1c and current diabetic medication
use (name, dose and frequency of medication) were self-reported in
the study app by participants. Participants were encouraged by
their coaches to report any changes to medications within their
study app. Email reminders were utilized to prompt entry of a
follow-up Hemoglobin A1c and updated medications at 12 weeks.
Medication and Hemoglobin A1c data were reviewed by two study
authors (NLG, MAB). Participants were contacted by study staff
(KLE, NLG) to help clarify potential reporting errors.
[0200] Engagement
[0201] Engagement with both the study app and coaching calls was
easured automatically via the study app. Total engagement is
defined as the average number of recorded app actions per day (e.g.
planning or reporting meals, scheduling calls, building shopping
lists, etc.).
[0202] Self-Efficacy
[0203] End of program self-efficacy to manage diabetes and to
maintain an optimal dietary pattern was measured via online survey
questions using a Likert scale; this was emailed to participants
during their 12th week.
[0204] Statistical Methods
[0205] Statistical analyses were performed using SAS software,
version 9.4 (SAS Institute Inc.). Change over time of continuous
variables was analyzed using two-tailed paired Student's t-test
with alpha set at 0.05 and chi-square tests for differences in
categorical variables. McNemar's test was used to evaluate
medication change.
[0206] To evaluate the combined effects of medication and HbA1c
change, we calculated a composite outcome measure defined as a
decrease in diabetic medication use without an increase in HbA1c,
or an improvement in HbA1c of at least 0.5% without an increase in
diabetic medication use.
[0207] We used mixed-effects modeling to test the effects of
baseline BMI, years since diagnosis of diabetes, net change in
diabetes medications, total app engagement and baseline HbA1c on
the mean change in HbA1c. To evaluate the intent-to-treat effect,
we used a last-value-carried-forward approach for the missing data
from participants who did not report follow-up Hemoglobin A1c's.
Since effect-size can be modulated by baseline HbA1c [31] we also
tested the effects of a log transformed HbA1c.
[0208] To investigate the relationship between engagement with the
program and HbA1c, we first defined tertiles of app engagement
using the sum of all actions taken in the app during the study. A
general linear regression was used to test the effect of app use
tertile with the change in HbA1c. Change in HbA1c was set as the
dependent variable with tertile of app engagement, and the log
transformed baseline HbA1c as independent variables. Using the
least square means pairwise comparison, we tested the differences
in changes in HbA1c by the tertiles of app engagement.
[0209] Results
[0210] Participants
[0211] 123 individuals with self-reported type 2 diabetes and an
initial Hemoglobin A1c of 6.5% or higher downloaded the
intervention app, of which 118 (95.9% of downloads) consented to
participation in the study. There were 9 dropouts (7.6% of
consented) during the study. Of the remaining 109 participants, 94
(86.2%) were still using the app at 12-weeks and 101 (92.7%)
provided some or all end-study data.
[0212] Baseline characteristics are summarized in Table 1.
Participants from 38 US states consented to participate. 81.4%
(n=96) were female, with a mean age of 50.7 years (SD 9.4) a mean
BMI of 38.1 kg/m2 (SD 8.8) and a mean Hemoglobin A1c of 8.1% (SD
1.6) at baseline. There were no statistical differences in baseline
characteristics between those who consented and those who submitted
end-study data.
TABLE-US-00001 TABLE 1 Sample characteristics at baseline by
program completion Submitted Completed End Study Total Program
Data.sup.a User Characteristics (n = 118) (n = 109) (n = 101)
P.sup.b Female, n (%) 96 (81.4) 87 (79.8) 80 (79.2) .14 Age
(years), mean (SD) 50.7 (9.4) 50.4 (9.6) 50.4 (9.7) .85 Geographic
distribution, 38 37 37 .71 # U.S. states Hemoglobin A1c 8.1 (1.6)
8.2 (1.6) 8.2 (1.7) .81 (%), mean (SD) Body mass index 38.1 (8.8)
38.4 (9.0) 38.1 (8.9) .99 (kg/m.sup.2), mean (SD) Time since
diabetes 2.6 (1.6) 2.6 (1.5) 2.6 (1.5) .99 diagnosis (years), mean
(SD) Diabetes medications 1.4 (0.9) 1.5 (0.9) 1.5 (0.9) .73
(count), mean (SD) .sup.aParticipants who submitted an end-study
Hemoglobin A1c and/or self-efficacy survey .sup.bP value comparing
total sample to those submitting end study data
[0213] Hemoglobin A1c
[0214] Among participants who reported an end-study Hemoglobin A1c,
80.4% (78/97) had improvement of Hemoglobin A1c, with 58.8% (57/97)
having a decrease of -0.5% or more, 39.2% (38/97) having a decrease
of 1% or more, and 22.7% (22/97) having a follow-up Hemoglobin
A1c<6.5%. The mean change was -0.8% (SD 1.3, P<0.001) over a
mean interval of 3.5 months (SD 0.9). This change remained
statistically significant in our mixed-effects model (P=0.003).
Substituting the log transformed baseline HbA1c we found that the
impact of baseline HbA1c was modulated and the significance of the
mean change in HbA1c was improved (P<0.001). Using a
last-value-carried-forward approach for the missing data from
participants who did not report follow-up Hemoglobin A1c's, the
mean change remained statistically significant (n=118, -0.6%, SD
0.9, P<0.001).
[0215] Among those with a baseline hemoglobin >7%, the mean
change was -1.0% (n=69, SD 1.4, P<0.001). Excluding those who
experienced a change in glycemic medication mid-study (n=2), the
mean change in HbA1c was -1.1% (n=65, SD 1.4, P<0.001).
[0216] Medication Use
[0217] At the start of the study, participants reported taking an
average of 1.4 diabetic medications (SD 0.9) with a self-reported
average time since diagnosis of 2.6 years (SD 1.6). Of those
reporting follow-up medication data (n=97), 4 (4.1%) changed
medications or dosages within the 12-week study (i.e. their
medication changes were likely to impact follow-up HbA1c). In
conjunction with reporting an end-study hemoglobin A1c, 16
participants (16.5%) reported decreasing or stopping one or more
diabetic medications and 8 (8.3%) increased or added one or more
diabetic medications. The frequency of decreased medication use
(either decreasing dose or stopping a medication) compared to
baseline medication use was statistically significant
(P<0.001).
[0218] Using the composite outcome measure defined above, 56.7% of
participants (55/97) met the composite outcome of reducing HbA1c,
reducing diabetic medication use or both.
[0219] Program Engagement
[0220] Of the 118 individuals who consented to participate, 109
(92.4%) were active in the study at the end of the 12-week
intervention period and 95 of 109 (86.2%) were still utilizing the
app. Total distinct app engagements averaged 4.3 per day (SD 2.5)
and average number of coaching calls completed was 4.1 (SD 1.8)
during the 12-week period.
[0221] We explored the relationship between app use and Hemoglobin
A1c change. As shown in FIG. 22, there was a stepwise decrease in
Hemoglobin A1c as app engagement level increased. For example, as
displayed in FIG. 1, in those with a baseline HbA1c>7.0% who did
not change medications during the study period, the lowest tertile
of engagers reduced HbA1c by 0.9% (SD 1.3); whereas, the highest
tertile of engagers reduced HbA1c by 1.3% (SD 1.0, P=0.03 using log
transformed baseline HbA1c).
[0222] Self-Efficacy
[0223] 98 participants answered questions pertaining to
self-efficacy. 90 participants (91.8% of those responding) reported
greater confidence in their ability to manage their diabetes
compared to before the program. 89 participants (90.8%) reported
greater confidence in their ability to maintain a healthy dietary
pattern. Table 2 summarizes change in Hemoglobin A1c, diabetes
medications and self-efficacy.
TABLE-US-00002 TABLE 2 Change in Hemoglobin A1c, diabetes
medications and self-efficacy Measures Value n P.sup.a Hemoglobin
A1c (%), mean -0.8 (1.3) 97 <.001 change (SD) Duration
(months).sup.b, mean (SD) 3.5 (0.8) 97 Decrease by 0.5% of more, %
58.8 57 Decrease by 1.0% of more, % 39.2 38 Decrease in diabetes
16.5 16 medication use.sup.c, % Increase in diabetes 8.3 8
medication use.sup.c, % Daily mobile app engagements.sup.d, 4.3
(2.5) 109 mean (SD) Diabetes self-efficacy.sup.c, 4.5 (0.6) 98 mean
(SD) Dietary change self-efficacy.sup.c, 4.4 (0.8) 98 mean (SD)
.sup.aComparison of baseline and end study values by paired
Student's t-test .sup.bTime between the baseline and end study
hemoglobin A1c values .sup.cIncludes those who changed dose and/or
number of medications used .sup.dIncludes use of all features in
the mobile app, does not count login .sup.eRated on a 5 point
Likert scale with 5 = a lot more confident and 1 = a lot less
confident
[0224] Discussion
[0225] In this study we examined the effectiveness of a digital
therapeutic delivered to participants with type 2 diabetes
distributed across the United States. We found clinically
meaningful reductions in both Hemoglobin A1c and the proportion of
participants who reduced diabetic medication usage at the
conclusion of the 12-week study period. We also observed greater
glycemic control in participants with higher levels of engagement
with the app.
[0226] The magnitude of Hemoglobin A1c reduction observed was
comparable to those found with commonly prescribed medications
(Sherifali et al. The Effect of Oral Antidiabetic Agents on A1c
Levels Diabetes Care 33(8):1859-1864 (2010)) as well as intensive
lifestyle interventions delivered in person. (Chen et al. Effect of
Lifestyle Intervention in patients with type 2 diabetes: A
meta-analysis Metabolism 64(2):338-347 (2015)) In addition, a
meaningful percentage (22.7%, 22/97) of participants achieved a
Hemoglobin A1c value below the diabetic range, 22.7% (5/22) of
which reported no diabetic medication use, indicating potential for
partial or complete remission of diabetes as defined by the ADA
consensus definition. The short duration of this trial and lack of
knowledge of the temporal sequence of lab test vs medication change
did not allow us to conclusively evaluate remission status.
Example 3
[0227] Fifteen subjects from the 12-week study described in Example
2 were selected for an extended study to determine the durability
of the clinical response observed in the results described in
Example 2. The extended study was conducted for an additional 18
weeks for a total of 30 weeks. As shown in Table 3, patients who
continued using the digital therapeutic exhibited sustained and
improved outcomes as compared to the 12-week study results
demonstrating that the methods described herein are effective for
chronic treatment of chronic disorders and/or chronic
lifestyle-related health conditions.
TABLE-US-00003 TABLE 3 n = 15 Mean (SD) Min Max A1c at baseline 8.6
(1.9) 6.5 12.3 A1c change at end intervention -1.1 (1.5) -3.8 0.8
A1c change since baseline -1.4 (1.8) -4.8 1.3 Weeks since baseline
23.9 (3.8) 18.0 33.4 A1c change since week 12 -0.3 (1.2) -1.0
3.8
[0228] Of the 15 who participated in extension, 6 have A1c values
that are in the prediabetes mellitus range (DM): 2 of these people
started in this group at baseline, 1 moved into this range during
the 12 week study, 3 moved into this range during the extension
(FIG. 23).
Example 4
[0229] In this study, we sought to understand to what degree a
novel, skill-focused, digital therapeutic program could reduce
diastolic and/or systolic blood pressure in hypertensive
subjects.
[0230] Methods
[0231] Eligibility criteria for participants included having a
self-reported diagnosis of hypertension, a baseline systolic blood
pressure (BP) of at least 130 mmHg and a diastolic blood pressure
of at least 80 mmHg measured within 14 days of program start, and
possession of an Android or iPhone Smartphone, as demonstrated by
the ability to download the intervention app. Participants were
excluded if they were not able to comply with the study protocol,
for example if they could not speak or read English or did not have
sufficient computer literacy to operate the app successfully.
[0232] Table 4 shows the results for participants who completed at
least one coach call during the study period. Change in systolic
and diastolic blood pressure were calculated as the average of the
most recent values available within 48 hours of each other minus
the baseline average value. Blood pressure duration was calculated
as the number of days between the first value and the most recent
value. Results are presented in graphic form in FIG. 24.
TABLE-US-00004 TABLE 4 Std N Variable N Mean Dev Min Max Miss
Initial Systolic BP avg 41 138.5 12.7 115 169 0 Final Systolic BP
avg 41 129.8 12.3 108 159 0 Initial Diastolic BP avg 41 86.3 7.7 65
102 0 Final Diastolic BP avg 41 81.0 10.5 60 104 0 Change in
Systolic 41 -8.7 12.3 -52 10.5 0 Change in Diastolic 41 -5.3 9.3
-31 15 0 Duration 41 51.6 29.7 4 91 0
[0233] Tertile analysis was performed to analyze the correlation
between app use engagement on reduction in blood pressure. 38 of
the 41 participants produced app use data and were included in the
tertile analysis. As shown in Tables 5 and 6, the lowest tertile of
engagement showed significantly less reduction in both systolic
(Table 5) and diastolic (Table 6) blood pressure as compared to the
highest tertile of engagement.
TABLE-US-00005 TABLE 5 Systolic Blood Pressure Std N Tertile N Mean
Dev Min Max Miss First (lowest engagement) 12 -4.7 13.1 -28 10.5 0
Second 13 -11.15 15.2 -52 5.5 0 Third 13 -10.7 9.3 -30 6.7 0
TABLE-US-00006 TABLE 6 Diastolic Blood Pressure Std N Tertile N
Mean Dev Min Max Miss First (lowest engagement) 12 -2.3 6.6 -10.3
15 0 Second 13 -5.7 11.0 -24 7 0 Third 13 -9.2 9.6 -31 3 0
[0234] Results were also stratified by baseline systolic blood
pressure. As illustrated in Tables 7-8, subjects exhibiting a
higher baseline blood pressure received a greater reduction in
blood pressure, demonstrating that both stage 1 and stage 2
hypertensive subjects benefit from the digital therapeutics
described herein.
TABLE-US-00007 TABLE 7 Systolic Blood Pressure Stage 1 Std N
Variable N Mean Dev Min Max Miss Initial Systolic Avg 18 129.0 4.2
122 135.8 0 Initial Diastolic Avg 18 82.7 6.4 65 89 0 Change in
Systolic 18 -3.5 9.1 -23 10.5 0 Change in Diastolic 18 -1.9 6.5
-12.3 15 0 Duration 18 45.4 30.0 7 88 0
TABLE-US-00008 TABLE 7 Systolic Blood Pressure Stage 2 Std N
Variable N Mean Dev Min Max Miss Initial Systolic Avg 23 146.0 12.1
115 169 0 Initial Diastolic Avg 23 89.1 7.6 68 102 0 Change in
Systolic 23 -12.8 13.1 -52 7.7 0 Change in Diastolic 23 -8.0 10.4
-31 7 0 Duration 23 56.4 29.2 4 91 0
[0235] While certain embodiments of the present invention have been
shown and described herein, it will be obvious to those skilled in
the art that such embodiments are provided by way of example only.
Numerous variations, changes, and substitutions will now occur to
those skilled in the art without departing from the invention. It
should be understood that various alternatives to the embodiments
of the invention described herein may be employed in practicing the
invention. It is intended that the following claims define the
scope of the invention and that methods and structures within the
scope of these claims and their equivalents be covered thereby.
* * * * *