U.S. patent application number 15/402839 was filed with the patent office on 2017-08-31 for medical system for seamless therapy adjustment.
The applicant listed for this patent is Medtronic, Inc.. Invention is credited to Tommy D. Bennett, Jennifer K. Bravinder, Shantanu Sarkar, Vinod Sharma, Lindsay M. Streeter, Eduardo N. Warman.
Application Number | 20170245794 15/402839 |
Document ID | / |
Family ID | 59678790 |
Filed Date | 2017-08-31 |
United States Patent
Application |
20170245794 |
Kind Code |
A1 |
Sharma; Vinod ; et
al. |
August 31, 2017 |
MEDICAL SYSTEM FOR SEAMLESS THERAPY ADJUSTMENT
Abstract
Methods and systems for seamless adjustment of treatment are
disclosed. A determination is made as to whether to intervene with
a patient's treatment. Implanted device memory data is acquired
over a pre-specified time period. Risk status is determined from
the device memory data. Another external device memory data is
acquired over a pre-specified time period. A determination is made
as to whether to adjust treatment of the patient in response to the
risk status, the data acquired from the implanted device memory and
the external device memory data.
Inventors: |
Sharma; Vinod; (Maple Grove,
MN) ; Warman; Eduardo N.; (Maple Grove, MN) ;
Sarkar; Shantanu; (Roseville, MN) ; Bennett; Tommy
D.; (Shoreview, MN) ; Streeter; Lindsay M.;
(Waconia, MN) ; Bravinder; Jennifer K.; (Denham
Springs, LA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Medtronic, Inc. |
Minneapolis |
MN |
US |
|
|
Family ID: |
59678790 |
Appl. No.: |
15/402839 |
Filed: |
January 10, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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62301303 |
Feb 29, 2016 |
|
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62435181 |
Dec 16, 2016 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/686 20130101;
G16H 40/40 20180101; A61B 5/076 20130101; G16H 40/63 20180101; A61B
5/6876 20130101; A61N 1/3627 20130101; A61B 5/053 20130101; A61B
5/021 20130101; A61B 5/7275 20130101; A61B 5/4848 20130101; A61B
5/4878 20130101; A61J 1/00 20130101; A61N 1/36521 20130101; A61N
1/36564 20130101; G16H 20/13 20180101; A61B 5/742 20130101; A61B
2560/0475 20130101; A61B 5/0205 20130101; A61N 1/3956 20130101;
G16H 20/10 20180101; A61B 5/7282 20130101; G16H 50/30 20180101;
A61B 5/6869 20130101; A61B 5/4842 20130101; A61B 5/4839 20130101;
G01G 19/44 20130101; A61B 5/0215 20130101; G16H 40/67 20180101 |
International
Class: |
A61B 5/00 20060101
A61B005/00; A61J 7/04 20060101 A61J007/04; A61J 7/00 20060101
A61J007/00; A61B 5/07 20060101 A61B005/07; A61B 5/0205 20060101
A61B005/0205 |
Claims
1. A system for determining whether to intervene with a patient's
treatment, the system comprising: an implantable device having a
memory; an implantable sensor; an implantable processor; an
external device; sensing means for sensing data through the
implanted sensor; the implanted processor configured to compare the
data against a threshold stored in the memory of the implanted
device to determine whether the data is considered to be indicative
of a heart failure (HF) worsening episode occurrence based on a
result of the comparison; storing means for storing a determined
occurrence in the memory of the implanted device; transmitting
means for transmitting the occurrence to the external device;
processing means for determining a risk status from the occurrence
and any other applicable data using the external device; means for
acquiring additional data, the additional data being one of weight,
symptoms, and blood pressure; and the external device configured to
automatically determine whether to adjust the patient's treatment
plan comprising a set of pharmaceutical physician prescriptions
based on the risk status, the data acquired from the implanted
device memory and the one or more other external devices the
external device further configured to signal a medication dispenser
to dispense a correct medication in response to determining to
adjust the patient's treatment plan.
2. The system of claim 1 wherein the additional data is acquired
from the external device or one or more other external devices.
3. The system of claim 2 wherein the additional data related to the
blood pressure is acquired from the implantable processor, another
implantable processor associated with another implantable device,
and a wireless pulmonary artery sensor.
4. The system of claim 2 wherein the additional data related to the
blood pressure is acquired from the external device or one or more
external devices.
5. A system of claim 1 wherein the implanted sensor is mechanically
and electrically connected to the implanted device.
6. A system of claim 1 wherein the implanted sensor is not
mechanically connected to the implanted device.
7. A system according to claim 1 further comprising: storing means
for storing a treatment plan into a memory of the external device,
the treatment plan comprising a first round of medication and a
second round of medication.
8. A system according to claim 6 wherein the treatment plan
comprises delivery of a prescribed medication, the prescribed
medication adjusted without directly communicating with the
patient's physician any time after storing the treatment plan into
memory.
9. A system of claim 1, further comprising: displaying means for
displaying the adjusted treatment on a graphical user interface in
response to determining that the patient's treatment requires
adjustment.
10. A system of claim 1, further comprising: means for acquiring
raw impedance data after a prescribed period of time in response to
adjusting the treatment of the patient; and means for using the raw
impedance data to determine whether the patient is improving in
response to the treatment.
11. A system of claim 1, further comprising: processing means for
determining whether the raw impedance data, acquired from the
implanted device memory, crosses a threshold; and in response to
determining whether the raw impedance data crosses the threshold,
determining whether the raw impedance data is considered a heart
failure exacerbation.
12. A system of claim 1, wherein the raw impedance data that is a
non-heart failure exacerbation does not require an intervention by
the healthcare system.
13. A system of claim 12, wherein the non-heart failure
exacerbation does not cause an adjustment to treatment.
14. A system of claim 12, wherein the non-heart failure
exacerbation triggers a notification to medical personnel.
15. A system of claim 12, wherein the non-heart failure
exacerbation does not trigger an intervention.
16. A system of claim 12, wherein the raw impedance data that is a
heart failure exacerbation that requires an intervention by the
healthcare system.
17. A system of claim 8, further comprising: processing means for
determining whether to terminate adjusted treatment in response to
data monitored after treatment was adjusted.
18. A system of claim 17, wherein termination of adjusted treatment
is based upon one of patient blood pressure, and symptoms.
19. A system of claim 1, further comprising: using the processor
from the external device to generate a notification for delivery of
a first round of medication.
20. A system of claim 1, further comprising: using the processor
from the external device to generate a notification for delivery of
a second round of medication.
21. A system of claim 15, further comprising: using the processor
from the external device to monitor one of the implanted device
memory data and the external device data after delivery of one of a
first or a second round of medication.
22. A system of claim 1, further comprising: using the processor
from the external device to generate a notification to one of
medical personnel and a patient for a blood sample to be acquired
and tested.
23. A system according to claim 1 further comprising: using the
processor from the external device to adjust therapy in response
determining weight loss.
24. A system according to claim 1 further comprising: using the
processor from the external device to adjust therapy in response
determining blood pressure and a symptom.
25. A system according to claim 1 wherein the adjusted therapy
involves cessation of one or more medications.
26. A system according to claim 23 wherein the adjusted therapy
involves one or more medications being increased in dosage.
27. A system according to claim 1 wherein one or more baseline
medications are examined.
28. A system according to claim 1 further comprising: using the
processor from the external device to determine whether one of a
set criteria has been met; and using the processor from the
external device to trigger review of one or more baseline
medications in response to determining whether one of a set
criteria has been met.
29. A system according to claim 26 wherein the one of the set
criteria comprises: (a) average pre-specified time period impedance
is less a threshold; (b) two or more medication interventions
occurred within a pre-specified amount of time; and (c) two or more
medication interventions were administered to the patient.
30. A system according to claim 27 wherein the threshold for the
average pre-specified time period impedance is less than or about
less than 66 Ohms.
31. A system according to claim 27 wherein the pre-specified time
period is about three months.
32. A system according to claim 7 wherein the treatment plan
comprises medication as a transient increase in diuretic or
vasodilator.
33. A method for determining whether to intervene with a patient's
treatment, the method comprising: (a) sensing data through an
implanted sensor; (b) using an implanted processor to measure the
data against a threshold stored in a memory of an implanted device
to determine whether the data is considered to be indicative of a
heart failure (HF) worsening episode occurrence; (c) storing the
occurrence in the memory of an implanted device; (d) transmitting
the occurrence to an external device; (e) determining risk status
from the occurrence and any other applicable data using the
external device; (f) acquiring additional data, the additional data
being related to one of weight, symptoms, and blood pressure; and
(g) using the external device to determine whether to adjust the
patient's treatment plan comprising a set of pharmaceutical
physician prescriptions in response to the risk status, the data
acquired from the implanted device memory and the one or more other
external devices, the external device configured to signal a user
device as to adjustment of a patient's treatment plan.
34. The method of claim 33 wherein the additional data is acquired
from one or more other external devices.
35. The method of claim 34 wherein the additional data related to
the blood pressure is acquired from the implantable processor or
another implantable processor associated with another implantable
device.
36. The method of claim 1 wherein the indication of the HF
worsening episode occurrence is based on a result of measuring the
sensed data against the threshold.
37. A method of claim 33 wherein the implanted sensor is
mechanically and electrically connected to the implanted
device.
38. A method of claim 33 wherein the implanted sensor is not
mechanically connected to the implanted device.
39. A method according to claim 33 further comprising: storing a
treatment plan into a memory of the external device, the treatment
plan comprising a first round of medication and a second round of
medication.
40. A method according to claim 39 wherein the treatment plan
comprises delivery of a prescribed medication, the prescribed
medication adjusted without directly communicating with the
patient's physician any time after storing the treatment plan into
memory.
41. A method of claim 33, further comprising: displaying the
adjusted treatment on a graphical user interface in response to
determining that the patient's treatment requires adjustment.
42. A method of claim 33, further comprising: acquiring raw
impedance data after a prescribed period of time in response to
adjusting the treatment of the patient; and using the raw impedance
data to determine whether the patient is improving in response to
the treatment.
43. A method of claim 33, further comprising: determining whether
the raw impedance data, acquired from the implanted device memory,
crosses a threshold; and in response to determining whether the raw
impedance data crosses the threshold, determining whether the raw
impedance data is considered a heart failure exacerbation.
44. A method of claim 42, wherein the raw impedance data that is a
non-heart failure exacerbation does not require an intervention by
a healthcare system.
45. A method of claim 42, wherein the non-heart failure
exacerbation does not cause an adjustment to treatment.
46. A method of claim 45, wherein the non-heart failure
exacerbation triggers a notification to medical personnel.
47. A method of claim 45, wherein the non-heart failure
exacerbation does not trigger an intervention.
48. A method of claim 45, wherein the raw impedance data that is a
heart failure exacerbation that requires an intervention by a
healthcare system.
49. A method of claim 39, further comprising: determining whether
to terminate adjusted treatment in response to data monitored after
treatment was adjusted.
50. A method of claim 49, wherein termination of adjusted treatment
is based upon one of patient blood pressure, and symptoms.
51. A method of claim 33, further comprising: generating a
notification for delivery of a first round of medication.
52. A method of claim 33, further comprising: generating a
notification for delivery of a second round of medication.
53. A method of claim 49, further comprising: monitoring one of the
implanted device memory data and the external device data after
delivery of one of a first or a second round of medication.
54. A method of claim 33, further comprising: generating a
notification to one of medical personnel and a patient for a blood
sample to be acquired and tested.
55. A method according to claim 33 further comprising: adjusting
therapy in response determining weight loss.
56. A method according to claim 33 further comprising: adjusting
therapy in response determining blood pressure and a symptom.
57. A method according to claim 33 wherein the adjusted therapy
involves cessation of one or more medications.
58. A method according to claim 55 wherein the adjusted therapy
involves one or more medications being increased in dosage.
59. A method according to claim 33 wherein one or more baseline
medications are examined.
60. A method according to claim 33 further comprising: determining
whether one of a set criteria has been met; and triggering review
of one or more baseline medications in response to determining
whether one of a set criteria has been met.
61. A method according to claim 58 wherein the one of the set
criteria comprises: (a) average pre-specified time period impedance
is less a threshold; (b) two or more medication interventions
occurred within a pre-specified amount of time; and (c) two or more
medication interventions were administered to the patient.
62. A method according to claim 59 wherein the threshold for the
average pre-specified time period impedance is less than or about
less than 66 Ohms.
63. A method according to claim 59 wherein the pre-specified time
period is about three months.
64. A method according to claim 34 wherein the treatment plan
comprises medication as a transient increase in diuretic or
vasodilator.
65. A method for determining whether to intervene with a patient's
treatment, the method comprising: (a) sensing data through an
implanted sensor; (b) using an implanted processor to measure the
data against a threshold stored in a memory of an implanted device
to determine whether the data is considered to indicative of an HF
episode occurrence; (c) storing the occurrence in the memory of an
implanted device; (d) transmitting the occurrence to an external
device; (e) determining risk status from the occurrence and any
other applicable data using the external device; (f) acquiring
additional data from one or more other external devices, the
additional data being related to one of weight, symptoms, and blood
pressure; and (g) using the external device to determine whether to
adjust treatment of the patient in response to the risk status; (h)
storing a treatment plan into a memory of the one or more external
devices, the treatment plan comprising a first round of medication
and a second round of medication, the treatment plan comprises a
prescribed medication, the prescribed medication adjusted without
being required to directly communicating with the patient's
physician any time after storing the treatment plan, the one or
more external devices configured to signal a patient's user device
indicating a change in the patient's treatment plan.
66. A system for determining whether to intervene with a patient's
treatment, the system comprising: an implantable device having a
memory; an implantable sensor; an implantable processor; an
external device; sensing means for sensing data through the
implanted sensor; the implanted processor configured to compare the
data against a threshold stored in the memory of the implanted
device to determine whether the data is considered to be indicative
of a heart failure (HF) worsening episode occurrence based on a
result of the comparison; storing means for storing a determined
occurrence in the memory of the implanted device; transmitting
means for transmitting the occurrence to the external device;
processing means for determining a risk status from the occurrence
and any other applicable data using the external device; means for
acquiring additional data, the additional data being one of weight,
symptoms, and blood pressure; the external device configured to
determine whether to adjust the patient's treatment based on the
risk status, the data acquired from the implanted device memory and
the one or more other external devices; and a treatment plan stored
into a memory of the one or more external devices or memory
associated with the external device, the treatment plan comprising
a first round of medication and a second round of medication, the
treatment plan comprises a prescribed medication, the prescribed
medication adjusted without being required to directly communicate
with the patient's physician any time after storing the treatment
plan into memory.
67. A system of claim 66, wherein an automatic drug dispenser in
configured to automatically deliver a proper dosage for a set of
prescribed medications,
68. A system of claim 67, wherein the automatic drug dispenser
withholds a previous dosage once the processor means determines
another dosage is required.
69. A system of claim 67 wherein the automatic drug dispenser is
configured to provide a set of containers, each container is
configured to store a unique dosage of medication from another
container of the set of containers.
70. A system for determining whether to intervene with a patient's
treatment, the system comprising: an implantable device having a
memory; an implantable sensor; an implantable processor; an
external device; sensing means for sensing data through the
implanted sensor; the implanted processor configured to compare the
data against a threshold(s) stored in the memory of the implanted
device to determine whether the data is considered to be indicative
of a heart failure (HF) worsening episode occurrence based on a
result of the comparison; storing means for storing a determined
occurrence in the memory of the implanted device; transmitting
means for transmitting the occurrence to the external device;
processing means for determining a risk status from the occurrence
and any other applicable data using the external device; means for
acquiring additional data, the additional data being one of weight,
symptoms, and blood pressure; the external device configured to
determine whether to adjust the patient's treatment based on a
prediction that worsening HF is occurring, the data acquired from
the implanted device memory, the external device or the one or more
other external devices; and a treatment plan stored into a memory
of the one or more external devices or memory associated with the
external device, the treatment plan comprising a first round of
medication and a second round of medication, the treatment plan
adjusted without being required to directly communicate with the
patient's physician any time after storing the treatment plan into
memory.
71. A system for determining whether to intervene with a patient's
treatment, the system comprising: an implantable device having a
memory; an implantable sensor; an implantable processor; an
external device; sensing means for sensing data through the
implanted sensor; the implanted processor configured to compare the
data against a threshold(s) stored in the memory of the implanted
device to determine whether the data is considered to be indicative
of a heart failure (HF) worsening episode occurrence based on a
result of the comparison; storing means for storing a determined
occurrence in the memory of the implanted device; transmitting
means for transmitting the occurrence to the external device;
processing means for predicting increased bodily fluid from the
occurrence and any other applicable data using the external device;
means for acquiring additional data, the additional data being one
of weight, symptoms, and blood pressure; the external device
configured to determine whether to adjust the patient's treatment
based on the prediction of increased fluid, the data acquired from
the implanted device memory, the external device or the one or more
other external devices; and a treatment plan stored into a memory
of the one or more external devices or memory associated with the
external device, the treatment plan comprising a first round of
medication and a second round of medication, the treatment plan
adjusted without being required to directly communicate with the
patient's physician any time after storing the treatment plan into
memory.
72. A system for determining whether to intervene with a patient's
treatment, the system comprising: an implantable device having a
memory; an implantable sensor; an implantable processor; an
external device; sensing means for sensing data through the
implanted sensor; the implanted processor configured to compare the
data against a threshold(s) stored in the memory of the implanted
device to determine whether the data is considered to be indicative
of a heart failure (HF) worsening episode occurrence based on a
result of the comparison; storing means for storing a determined
occurrence in the memory of the implanted device; transmitting
means for transmitting the occurrence to the external device;
processing means for predicting worsening HF from the occurrence
and any other applicable data using the external device; means for
acquiring additional data, the additional data being one of weight,
symptoms, and blood pressure; the external device configured to
determine whether to adjust the patient's treatment based on the
prediction of worsening HF, the data acquired from the implanted
device memory, the external device or the one or more other
external devices; and a treatment plan stored into a memory of the
one or more external devices or memory associated with the external
device, the treatment plan comprising a first round of medication
and a second round of medication, the treatment plan adjusted
without being required to directly communicate with the patient's
physician any time after storing the treatment plan into memory.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Application No. 62/301,313, filed on Feb. 29, 2016 and US
Provisional Application No. 62/435,181 filed on Dec. 17, 2016. The
disclosure of the above applications are incorporated herein by
reference in their entirety.
TECHNICAL FIELD
[0002] The present disclosure relates to a medical system, and,
more particularly, to a medical system configured to determine
whether to intervene with a patient's treatment.
BACKGROUND
[0003] Chronic heart failure (CHF) is a serious condition that
occurs when a heart is unable to consistently pump blood at an
adequate rate. To improve the ability of the heart to pump blood,
CHF patients may require an implantable medical device (IMD). IMDs
such as implantable cardioverter defibrillators (ICDs) or
pacemakers are capable of delivering cardiac resynchronization
therapy for improving a CHF patient's heart function. Despite using
IMDs to improve heart function, CHF patients may progressively
deteriorate, as evidenced by weight gain, change in blood pressure,
malaise, fatigue, swelling, fainting, and/or palpitations.
[0004] Patient data are obtained in a variety of ways. Typically, a
patient directly conveys health data to medical personnel during an
office visit. Some data may be automatically generated and sent
over the Internet to a computer system or health care system. For
example, electronic weight scales are configured to weigh a patient
and then automatically transmit that data to the health care
system.
[0005] In response to the collected data, healthcare systems can
respond in a variety of ways. Some healthcare systems are able to
generate health alerts based upon data detected by an IMD. One
exemplary healthcare system relates to US Patent Application US
2010-0030293 A1 to Sarkar et al. that is capable of generating
alerts for a patient to seek medical treatment in response to
detected information. For example, a medical device may detect
worsening heart failure in the patient based on a diagnostic
parameter. Upon detecting worsening heart failure, the medical
device may, for example, provide an alert that enables the patient
to seek medical attention before experiencing a heart failure
event.
[0006] While numerous healthcare systems are able to automatically
notify health care workers of potential health issues such as that
which is described in US Patent Application US 2010-0030293 A1 to
Sarkar et al., a healthcare system typically requires a physician's
input to adjust therapy (i.e. medication) delivered to a patient.
It is desirable to develop a healthcare system that is able to
seamlessly respond to a patient's deteriorating health conditions
without directly contacting a physician.
SUMMARY OF THE DISCLOSURE
[0007] Methods and systems are disclosed for seamless adjustment of
therapy delivered to a patient. Therapy (e.g. medication) is
adjusted without direct real time input by the physician. Instead,
the computer system causes preauthorized prescriptions from the
physician to be implemented based upon one or more conditions.
After one or more conditions are met, a nurse or a computer system
sends a message to the patient that an adjustment is needed to
their prescription medication. In the scenario involving a computer
sent message, the message transmission can be performed
automatically upon meeting one or more conditions. The patient has
the medication stored within his environment (e.g. home, office
etc.) and can take the newly prescribed medication such as
non-addictive medication, incremental dose of medication and/or
addition/removal of medication.
[0008] To determine whether to intervene with the therapy delivered
to a patient, a series of steps are implemented. For example, data
are acquired from an implanted device memory over a pre-specified
time period. A patient's heart failure (HF) risk status is then
determined from the device memory data (e.g. weight, symptoms
and/or blood pressure). Data is acquired from the external device,
another external device memory and/or an implantable medical device
over a pre-specified time period. A determination is then made as
to whether to adjust treatment of the patient in response to a
patient's heart failure (HF) risk status, the data acquired from
the implanted device memory, and the external device memory
data.
[0009] The present disclosure achieves numerous benefits over
conventional healthcare systems. For example, the healthcare system
is configured to adjust therapy without directly contacting the
physician immediately and/or in real-time before adjusting the
therapy. By adjusting therapy without first contacting the
physician, time spent by the physician, the patient and the
patient's caretaker are reduced compared to conventional health
care systems that requires the patient to physically visit the
doctor whenever the patient's diuretics require adjustment.
Additionally, the patient will be administered the proper
medication in a more timely fashion thereby reducing or avoiding
worsening HF condition.
BRIEF DESCRIPTION OF DRAWINGS
[0010] FIG. 1 is a block diagram illustrating an example computer
system that includes an external device and one or more computing
devices that are coupled to the IMD and programmer shown in FIG. 1
via a network.
[0011] FIG. 2 is a diagram of the exemplary IMD shown in FIG.
1.
[0012] FIG. 3 is a functional block diagram of the exemplary IMD
shown in FIG. 1.
[0013] FIG. 4 is a flow diagram of an exemplary symptom management
intervention process controlled by a medical system that can cause
one or more adjustments to therapy that is being delivered to a
patient.
[0014] FIG. 5 is a block diagram of integrated diagnostics related
to risk status.
[0015] FIG. 6 is a diagram depicting exemplary recovery on a daily
basis relative to a reference threshold.
[0016] FIG. 7 depicts medium risk status relative to a set of
exemplary risk factors.
[0017] FIG. 8 depicts high risk status relative to a set of
exemplary risk factors.
[0018] FIG. 9 is a block diagram of a patient's medication
dispenser.
DETAILED DESCRIPTION
[0019] Exemplary systems, methods, and interfaces shall be
described with reference to FIGS. 1-9. It will be apparent to one
skilled in the art that elements or processes from one embodiment
may be used in combination with elements or processes of the other
embodiments, and that the possible embodiments of such methods,
apparatus, and systems using combinations of features set forth
herein is not limited to the specific embodiments shown in the
figures and/or described herein. Further, it will be recognized
that the embodiments described herein may include many elements
that are not necessarily shown to scale. Still further, it will be
recognized that timing of the processes and the size and shape of
various elements herein may be modified but still fall within the
scope of the present disclosure, although certain timings, one or
more shapes and/or sizes, or types of elements, may be advantageous
over others. FIGS. 1-3 disclose a system for intervening into the
therapy delivered to the patient while FIG. 4 discloses a flow
diagram, controlled by the system, for an intervention to modify
the therapy delivered to a patient.
[0020] FIG. 1 is a block diagram illustrating an exemplary computer
system 100 that can seamlessly trigger the adjustment of a
patient's treatment plan without directly communicating with the
patient's physician any time after the treatment plan has been sent
to a centralized communication center for storage or stored into a
memory of a computing device. The treatment plan, stored at the
centralized communication center or in the memory of a server, can
comprise one or more rounds of medication (e.g., a first round of
medication, a second round of medication etc.). Generally,
adjusting treatment of the patient depends on the patient's risk of
a HF event, and data acquired from IMD 16, computing devices 102a-n
and/or programmer 24. A HF event is when a patient was admitted to
the hospital for worsening HF or the patient has received
Intravenous HF therapy (e.g. IV diuretics/vasodilators),
ultrafiltration at any settings including an emergency department,
ambulance, observation unit, urgent care, HF/Cardiology Clinic or
the patient's home. Communication of the adjusted treatment can be
delivered either electronically or via nurse to the patient.
[0021] Computer system 100 includes one or more computing devices
102a-102n, a programmer 24, a server 130, a network 110, and access
point 112. Network 110 may generally be used to transmit
information or data (e.g., physiological data, risk level data,
recovery data) between IMD 16 to other external computing devices
102a-c. However, network 110 may also be used to transmit
information from IMD 16 to an external computing device (e.g.
CARELINK.RTM.). Exemplary computer systems and/or features that can
implement the present disclosure include U.S. Pat. No. 8,585,604 to
Bennett et al., U.S. Pat. No. 6,970, 742 to Mann et al., Ritzema et
al, Physician-Directed Patient Self-Management of Left Atrial
Pressure in Advanced Chronic Heart Failure, Circulation, 2010, U.S.
Pat. No. 7,577,475 to Cosentino et al,--System, method, and
apparatus for combining information from an implanted device with
information from a patient monitoring apparatus, 2009, the
disclosure of each are incorporated by reference in their
entirety.
[0022] IMD 16 may use its telemetry module 88, described below
relative to FIG. 3, to communicate with computing devices 102a-n
("n" being any whole number of computing devices), server 130,
programmer 24. Typically, a wireless connection is employed. In one
example of FIG. 1, access point 110, programmer 24, external device
102n, and computing devices 102a-102n can be interconnected, and
able to communicate with each other, through network 112. In some
cases, one or more of access point 110, programmer 24, external
device 102n, and computing devices 102a-102n may be coupled to
network 112 through one or more wireless connections.
[0023] Another example of a computing device 102n may be a
patient's medication or drug dispenser 102, as shown in FIG. 7. The
computerized drug dispenser 102 includes a set of compartments, in
which each compartment 103a-d stores one or more medications at a
prescribed dosage. The drug dispenser if further configured to
receive instructions from the server to ensure that the patient has
access to the correct medication and/or dosage of medication. Once
the server determines a medication for a patient needs to be
adjusted, the server automatically signals the computing device
102n to automatically adjust delivery of the medication. For
example, assume that the patient requires a reduced dosage of a
medication. The server signals the computing device 102n to adjust
the dosage delivered to a patient.
[0024] The computing device 102n automatically switches from the
first to a second dosage compartments for drug delivery. The
medication delivery device rotates from the first dosage
compartment that stores a first dosage to the second dosage
compartment that stores a second dosage for delivery to the
patient. The medication delivery device automatically notifies the
patient there has been a modification in his or her dosage. The
medication delivery device then automatically notifies the patient
to take the medication during the day. The drug is automatically
dispensed to the patient at the proper dosage. The dispenser can be
set to automatically lock drug delivery once the proper dosage has
been delivered.
[0025] IMD 16, programmer 24, external device 102n, and computing
devices 102a-102n may each comprise one or more processors, such as
one or more microprocessors, DSPs, ASICs, FPGAs, programmable logic
circuitry, or the like, that may perform various functions and
operations, such as those described herein. Each processor can be
configured to perform some type of analog to digital conversion
(ADC) so that signals can be compared to some threshold. The signal
can be filtered before or after digitizing the signal. Other
applicable signal processing may also be applied.
[0026] Computing devices 102a-102n may comprise devices such as
servers, computers, weight scales, portable blood pressure
machines, biometric data collecting device, a computer, a symptom
assessment system, a personal digital assistant (e.g. cell phone,
iPad, or the like). In some examples, computing devices 102a-n may
generate data that are used by server to perform any of the various
functions or operations described herein, e.g., generate a heart
failure risk status based on the patient metric comparisons or
create patient metrics from the raw metric data. Computing devices
102a-n include input/output device 104c, processor 106b and memory
108c.
[0027] Each computing device includes an input/output device
104a-c, a processor, 106a-c, and memory 108a-c. Input/output device
116 includes input devices such as a keyboard, a mouse, voice
input, sensor for weight, etc. and output device includes graphical
user interfaces, printers and other suitable means. Processor
106a-c or 134 includes any suitable processor. The processor 134
can be configured to perform some type of analog to digital
conversion so that signal can be compared to some threshold.
Processor 134 is configured to perform a variety of functions such
as calculations, accessing data from memory performing comparisons,
setting the start and end dates for each evaluation period etc. The
evaluation period serves as an evaluation window that encompasses
data, acquired from each patient, that are within the boundaries
(i.e. start and end times). Exemplary calculations performed by
processor 106a-c can be calculating risk of a heart failure event
for each evaluation period.
[0028] Memory 108a-c may include any volatile, non-volatile,
magnetic, optical, or electrical media, such as a random access
memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM),
electrically-erasable programmable ROM (EEPROM), flash memory, or
any other digital or analog media. Memory 108a-c stores data.
Exemplary data stored in memory 108a-c includes heart failure
patient data, heart failure prospective risk data, intracardiac or
intravascular pressure, activity, posture, respiration, thoracic
impedance, impedance trend, risk of hypervolemia or hypovolemia
etc. Evaluation period start and end times are also stored in
memory. Heart failure patient data includes data observations (e.g.
data sensed from sensors that cross a threshold). Additionally,
evaluation period data is also stored in memory 108a-c. For
example, the start and end dates of the evaluation period data is
stored in memory 108a-c.
[0029] Programmer 24 can include any appropriate programming
system, including one generally known to those skilled in the art,
such as the Medtronic CARELINK.TM. programmer, sold by Medtronic,
Plc. of Minneapolis, MN. Programmer 24 may communicate wirelessly
with IMD 16, such as using RF communication or proximal inductive
interaction. This wireless communication is possible through the
use of telemetry module, which may be coupled to an internal
antenna or an external antenna. An external antenna that is coupled
to programmer 24 may correspond to the programming head that may be
placed over heart. The telemetry module may also be configured to
communicate with another computing device via wireless
communication techniques, or direct communication through a wired
connection. Examples of local wireless communication techniques
that may be employed to facilitate communication between programmer
24 and another computing device include RF communication according
to the 102.11 or Bluetooth specification sets, infrared
communication, e.g., according to the IrDA standard, or other
standard or proprietary telemetry protocols. In this manner, other
external devices may be capable of communicating with programmer 24
without needing to establish a secure wireless connection. An
additional computing device in communication with programmer 24 may
be a networked device such as a server capable of processing
information retrieved from IMD 16.
[0030] In this manner, programmer telemetry module (not shown) may
transmit an interrogation request to telemetry module of IMD 16.
Accordingly, the telemetry module may receive data (e.g. diagnostic
information, real-time data related to absolute intrathoracic
impedance that may be indicative of hypervolemia or hypovolemia,
etc.) or diagnostic information selected by the request or based on
already entered patient status to IMD 16. The data may include
patient metric values or other detailed information from telemetry
module of IMD 16. The data may include an alert or notification of
the heart failure risk level from the telemetry module of IMD 16.
The alert may be automatically transmitted, or pushed, by IMD 16
when the heart failure risk level becomes critical. In addition,
the alert may be a notification to a healthcare professional, e.g.,
a clinician or nurse, of the risk level and/or an instruction to
patient 14 to seek medical treatment (e.g. testing to confirm
worsening HF etc.). In response to receiving the alert, the user
interface may display the alert to the healthcare professional
regarding the risk level or present an instruction to patient 14 to
seek medical treatment.
[0031] Either in response to heart failure data, e.g., the risk
level or patient metrics, or requested heart failure information,
the user interface for a computing device or programmer 24 may
present the patient metrics, the heart failure risk level, or
recommended treatment (e.g. medication) to the user. In some
examples, the user interface may also highlight each of the patient
metrics that have exceeded the respective one of the plurality of
metric-specific thresholds. In this manner, the user may quickly
review those patient metrics that have contributed to the
identified heart failure risk level.
[0032] Access point 110 may comprise a device that connects to
network 112 via any of a variety of connections, such as telephone
dial-up, digital subscriber line (DSL), or cable modem connections.
In other examples, access point 110 may be coupled to network 112
through different forms of connections, including wired or wireless
connections. In some examples, access point 110 may be co-located
with patient 14 and may comprise one or more programming units
and/or computing devices (e.g., one or more monitoring units) that
may perform various functions and operations described herein.
[0033] In another example, access point 110 may be a LINQ.TM.
device co-located within the patient and configured to sense,
record and transmit data to network 110. Alternatively, SEEQ.TM.,
configured for monitoring, maybe attached to the skin of the
patient. In another example, access point 110 may include a
home-monitoring unit that is located within patient 14 and that may
monitor the activity of IMD 16. LINQ.TM. and SEEQ.TM. commercially
available from Medtronic, Inc. located in Minneapolis, Minn. may
also be used as access point 110. An example of such a LINQ.TM. may
be seen with respect to U.S. Pregrant Publication No. 2016-0310031
A1 filed Apr. 20, 2016, and assigned to the assignee of the present
invention, the disclosure of which is incorporated by reference in
its entirety herein.
[0034] Server 130 can be located at a centralized communication
center such as at Cardiocom.RTM.. Server 130 is configured to
perform complex computations for a large group of patients and
provides secure storage in memory 136 for archival of information
(e.g., patient metric data, heart failure risk levels, weight,
blood pressure etc.) setup in a database 132 that has been
collected and generated from IMD 16, programmer 24 and/or external
devices. Exemplary medium and high risk calculations are shown and
described in US 2016-0361026 A1 (U.S. app. Ser. No. 13/391,376)
entitled METHOD AND APPARATUS FOR MONITORING TISSUE FLUID CONTENT
FOR USE IN AN IMPLANTABLE CARDIAC DEVICE and US2012032243 (U.S.
app. Ser. No. 12/914,836 filed Oct. 28, 2010), entitled HEART
FAILURE MONITORING AND NOTIFICATION and assigned to the assignee of
the present invention, the disclosure of which is incorporated by
reference in its entirety herein.
[0035] Examples of medium and high risk status are presented in
FIGS. 7-8. Medium risk status, for example, may involve one or more
conditions such as AT/AF burden exceeding a threshold value (>6
hours/day), low % V pacing and high night heart rate (>85 bpm).
High risk status, for example, may involve one or more conditions
such as high OptiVol.TM./impedance index (>60 ohm-days), patient
activity (<1 hour/day), high night heart rate (>85 bpm) and
low HRV (<60 ms).
[0036] Memory 136 stores a set of diagnostic metrics indicative of
worsening heart failure for each patient. Diagnostic metrics or
metrics can include a variety of data. Exemplary data, shown in
FIG. 5, includes (1) impedance trend index commercially available
in IMDs from Medtronic Plc., located in MN), (2) intrathoracic
impedance, (3) atrial tachycardia/atrial fibrillation (AT/AF)
burden, (4) mean ventricular rate during AT/AF, (5) patient
activity, (6) ventricular (V) rate, (7) day and night heart rate,
(8) percent CRT pacing, and/or (9) number of shocks. The impedance
index is an indicator of the amount of fluid congestion experienced
by the patient. The impedance index is the difference between an
impedance measured during real time using IMD 16 and a reference
impedance, that can be continuously updated, established by the IMD
16 or during another visit to the physician. The impedance index is
described in greater detail with respect to U.S. pat. Ser. No.
10/727,008 filed on Dec. 3, 2003 issued as U.S. Pat. No. 7,986,994,
and assigned to the assignee of the present invention, the
disclosure of which is incorporated by reference in its entirety
herein.
[0037] Heart rate variability (HRV) is a marker of autonomic tone
and has been shown to provide prognostic information for mortality
risk. A decrease in HRV is associated with increased sympathetic
tone. Using HRV device diagnostic data, patients with low HRV
(<100 ms) are at a higher combined risk of death and
hospitalization. Patients with HRV <50 ms exhibit an even higher
risk than those with HRV in the range of 50-100 ms.
[0038] Similar to HRV, elevated heart rate is a marker of elevated
sympathetic tone and has been shown to have prognostic value for
worsening HF. Night Heart Rate (NHR), measured between midnight and
4 AM, can be a better metric than the day time heart rate. Day time
heart rate can be affected by varying activity level (e.g. rest and
exercise). Patients with high NHR (75.+-.25 bpm) typically
experience higher risk of being hospitalized or dying than those
who had low NHR (73.+-.11 bpm) [Additionally, declining patient
activity is associated with worsening HF status and can potentially
be of value for predicting HF hospitalization. Declining patient
activity can be determined by a variety of activity devices such as
a FITBIT, cellphone etc.
[0039] Combination variables (e.g. combining pacing and arrhythmia
related information) can also be used to evaluate worsening HF
risk. For example, one of the components of combination variable is
substantial decrease (>8%) in CRT pacing, which is associated
with high HF events. A decline in CRT pacing can occur because of
rapid conduction during AF. Thus, mean ventricular rate 90 bpm and
atrial fibrillation (AF) burden 6 hours/day and shocks delivered to
Ventricular Fibrillation/Ventricular Tachycardia (VT/VF) can also
be components of the combination variable.
[0040] IMD 16, programmer 24, and/or computing devices a-n may
communicate via wireless communication using any techniques known
in the art. Examples of communication techniques may include, for
example, radiofrequency (RF) telemetry, but other communication
techniques such as magnetic coupling are also contemplated. In some
examples, programmer 24 may include a programming head that may be
placed proximate to the body of the patient near the IMD 16 implant
site in order to improve the quality or security of communication
between IMD 16 and programmer 24.
[0041] Network 110 may comprise a local area network, wide area
network, or global network, such as the Internet. In some cases,
programmer 24 or external server 130 may assemble the diagnostic
data, heart failure data, prospective heart failure risk data or
other suitable data in web pages or other documents for viewing by
and trained professionals, such as clinicians, via viewing
terminals associated with computing devices 120. The system 100 of
FIG. 1 may be implemented, in some aspects, with general network
technology and functionality similar to that provided by the
Medtronic CareLink.RTM. Network developed by Medtronic, Plc., of
Minneapolis, Minn.
[0042] FIG. 2 is an enlarged view of IMD 16, which is coupled to
leads 18, 20, and 22 and programmer 24. IMD 16 may be, for example,
an implantable pacemaker, cardioverter, and/or defibrillator that
provides electrical signals to heart 12 via electrodes coupled to
one or more of leads 18, 20, and 22. Patient 14 is ordinarily, but
not necessarily a human patient. In general, the techniques
described in this disclosure may be implemented by any medical
device, e.g., implantable or external, that senses a signal
indicative of cardiac activity, patient 14 activity, and/or fluid
volume within patient 14. As one alternative example, the
techniques described herein may be implemented in an external
cardiac monitor that generates electrograms of heart 12 and detects
thoracic fluid volumes, respiration, and/or cardiovascular pressure
of patient 14.
[0043] Leads 18, 20, 22 extend into the heart 12 of patient 14 to
sense electrical activity of heart 12 and/or deliver electrical
stimulation to heart 12. Leads 18, 20, and 22 may also be used to
detect a thoracic impedance indicative of fluid volume in patient
14, respiration rates, sleep apnea, or other patient metrics.
Respiration metrics, e.g., respiration rates, tidal volume, and
sleep apnea, may also be detectable via an electrogram, e.g., based
on a signal component in a cardiac electrogram that is associated
with respiration. In the example shown in FIG. 1, right ventricular
(RV) lead 18 extends through one or more veins (not shown), the
superior vena cava (not shown), and right atrium 26, and into right
ventricle 28. Left ventricular (LV) coronary sinus lead 20 extends
through one or more veins, the vena cava, right atrium 26, and into
the coronary sinus 30 to a region adjacent to the free wall of left
ventricle 32 of heart 12. Right atrial (RA) lead 22 extends through
one or more veins and the vena cava, and into the right atrium 26
of heart 12.
[0044] In some examples, system 100 may additionally or
alternatively include one or more leads or lead segments (not shown
in FIG. 2) that deploy one or more electrodes within the vena cava,
or other veins. Furthermore, in some examples, system 100 may
additionally or alternatively include temporary or permanent
epicardial or subcutaneous leads with electrodes implanted outside
of heart 12, instead of or in addition to transvenous, intracardiac
leads 18, 20 and 22. Such leads may be used for one or more of
cardiac sensing, pacing, or cardioversion/defibrillation. For
example, these electrodes may allow alternative electrical sensing
configurations that provide improved or supplemental sensing in
some patients. In other examples, these other leads may be used to
detect intrathoracic impedance as a patient metric for identifying
a heart failure risk or fluid retention levels.
[0045] IMD 16 may sense electrical signals attendant to the
depolarization and repolarization of heart 12 via electrodes (not
shown in FIG. 1) coupled to at least one of the leads 18, 20, 22.
In some examples, IMD 16 provides pacing pulses to heart 12 based
on the electrical signals sensed within heart 12. The
configurations of electrodes used by IMD 16 for sensing and pacing
may be unipolar or bipolar. IMD 16 may detect arrhythmia of heart
12, such as tachycardia or fibrillation of the atria 26 and 36
and/or ventricles 28 and 32, and may also provide defibrillation
therapy and/or cardioversion therapy via electrodes located on at
least one of the leads 18, 20, 22. In some examples, IMD 16 may be
programmed to deliver a progression of therapies, e.g., pulses with
increasing energy levels, until a fibrillation of heart 12 is
stopped. IMD 16 may detect fibrillation employing one or more
fibrillation detection techniques known in the art.
[0046] In addition, IMD 16 may monitor the electrical signals of
heart 12 for patient metrics stored in IMD 16 and/or used in
generating the heart failure risk level. IMD 16 may utilize two of
any electrodes carried on leads 18, 20, 22 to generate electrograms
of cardiac activity. In some examples, IMD 16 may also use a
housing electrode of IMD 16 (not shown) to generate electrograms
and monitor cardiac activity. Although these electrograms may be
used to monitor heart 12 for potential arrhythmias and other
disorders for therapy, the electrograms may also be used to monitor
the condition of heart 12. For example, IMD 16 may monitor heart
rate (night time and day time), heart rate variability, ventricular
or atrial intrinsic pacing rates, indicators of blood flow, or
other indicators of the ability of heart 12 to pump blood or the
progression of heart failure.
[0047] In some examples, IMD 16 may also use any two electrodes of
leads 18, 20, and 22 or the housing electrode to sense the
intrathoracic impedance of patient 14. As the tissues within the
thoracic cavity of patient 14 increase in fluid content, the
impedance between two electrodes may also change. For example, the
impedance between an RV coil electrode and the housing electrode
may be used to monitor changing intrathoracic impedance.
[0048] IMD 16 may use intrathoracic impedance to create a fluid
index. As the fluid index increases, more fluid is being retained
within patient 14 and heart 12 may be stressed to keep up with
moving the greater amount of fluid. Therefore, this fluid index may
be a patient metric transmitted in diagnostic data or used to
generate the heart failure risk level. By monitoring the fluid
index in addition to other patient metrics, IMD 16 may be able to
reduce the number of false positive heart failure identifications
relative to what might occur when monitoring only one or two
patient metrics. Furthermore, IMD 16, along with other networked
computing devices described herein, may facilitate remote
monitoring of patient 14, e.g., monitoring by a health care
professional when the patient is not located in a healthcare
facility or clinic associated with the health care professional,
during a post-hospitalization period. An example system for
measuring thoracic impedance and determining a fluid index is
described in U.S. Pat. No. 8,255,046 to Sarkar et al., entitled,
"DETECTING WORSENING HEART FAILURE BASED ON IMPEDANCE
MEASUREMENTS," which published on Feb. 4, 2010 and is incorporated
herein by reference in its entirety.
[0049] Whether a patient begins to experience or is experiencing HF
symptoms is based upon a variety of parameters that can change over
time. Exemplary parameters capable of changing over time includes
the patient's weight (i.e. extreme weight loss), hypotension,
syncope, pre-syncope, all of which can be uploaded to the system
100 on a periodic basis (e.g. daily, weekly, monthly etc.) from the
patient's computer and/or user device 102a-n.
[0050] FIG. 3 is a functional block diagram illustrating an example
configuration of IMD 16. In the illustrated example, IMD 16
includes a processor 80, memory 82, metric detection module 92,
signal generator 84, sensing module 86, telemetry module 88, and
power source 90. Memory 82 includes computer-readable instructions
that, when executed by processor 80, cause IMD 16 and processor 80
to perform various functions attributed to IMD 16 and processor 80
herein. Memory 82 may include any volatile, non-volatile, magnetic,
optical, or electrical media, such as a random access memory (RAM),
read-only memory (ROM), non-volatile RAM (NVRAM),
electrically-erasable programmable ROM (EEPROM), flash memory, or
any other digital or analog media.
[0051] Processor 80 may include any one or more of a
microprocessor, a controller, a digital signal processor (DSP), an
application specific integrated circuit (ASIC), a
field-programmable gate array (FPGA), or equivalent discrete or
analog logic circuitry. In some examples, processor 80 may include
multiple components, such as any combination of one or more
microprocessors, one or more controllers, one or more DSPs, one or
more ASICs, or one or more FPGAs, as well as other discrete or
integrated logic circuitry. The functions attributed to processor
80 herein may be embodied as software, firmware, hardware or any
combination thereof.
[0052] Processor 80 controls signal generator 84 to deliver
stimulation therapy to heart 12 according to a therapy parameters,
which may be stored in memory 82. For example, processor 80 may
control signal generator 84 to deliver electrical pulses with the
amplitudes, pulse widths, frequency, or electrode polarities
specified by the therapy parameters.
[0053] Signal generator 84 is electrically coupled to electrodes
40, 42, 44, 46, 48, 50, 58, 62, 64, and 66, e.g., via conductors of
the respective lead 18, 20, 22, or, in the case of housing
electrode 58, via an electrical conductor disposed within housing
60 of IMD 16. In the illustrated example, signal generator 84 is
configured to generate and deliver electrical stimulation therapy
to heart 12. For example, signal generator 84 may deliver
defibrillation shocks to heart 12 via at least two electrodes 58,
62, 64, 66. Signal generator 84 may deliver pacing pulses via ring
electrodes 40, 44, 48 coupled to leads 18, 20, and 22,
respectively, and/or helical electrodes 42, 46, and 50 of leads 18,
20, and 22, respectively. In some examples, signal generator 84
delivers pacing, cardioversion, or defibrillation stimulation in
the form of electrical pulses. In other examples, signal generator
may deliver one or more of these types of stimulation in the form
of other signals, such as sine waves, square waves, or other
substantially continuous time signals.
[0054] Signal generator 84 may include a switch module and
processor 80 may use the switch module to select, e.g., via a
data/address bus, which of the available electrodes are used to
deliver defibrillation pulses or pacing pulses. The switch module
may include a switch array, switch matrix, multiplexer, or any
other type of switching device suitable to selectively couple
stimulation energy to selected electrodes.
[0055] Electrical sensing module 86 monitors signals from at least
one of electrodes 40, 42, 44, 46, 48, 50, 58, 62, 64 or 66 in order
to monitor electrical activity of heart 12, impedance, or other
electrical phenomenon. Sensing may be done to determine heart rates
or heart rate variability, or to detect arrhythmias or other
electrical signals. Sensing module 86 may also include a switch
module to select which of the available electrodes are used to
sense the heart activity, depending upon which electrode
combination, or electrode vector, is used in the current sensing
configuration. In some examples, processor 80 may select the
electrodes that function as sense electrodes, i.e., select the
sensing configuration, via the switch module within sensing module
86. Sensing module 86 may include one or more detection channels,
each of which may be coupled to a selected electrode configuration
for detection of cardiac signals via that electrode configuration.
Some detection channels may be configured to detect cardiac events,
such as P- or R-waves, and provide indications of the occurrences
of such events to processor 80, e.g., as described in U.S. Pat. No.
5,117,824 to Keimel et al., which issued on Jun. 2, 1992 and is
entitled, "APPARATUS FOR MONITORING ELECTRICAL PHYSIOLOGIC
SIGNALS," and is incorporated herein by reference in its entirety.
Processor 80 may control the functionality of sensing module 86 by
providing signals via a data/address bus.
[0056] Processor 80 may include a timing and control module, which
may be embodied as hardware, firmware, software, or any combination
thereof. The timing and control module may comprise a dedicated
hardware circuit, such as an ASIC, separate from other processor 80
components, such as a microprocessor, or a software module executed
by a component of processor 80, which may be a microprocessor or
ASIC. The timing and control module may implement programmable
counters. If IMD 16 is configured to generate and deliver pacing
pulses to heart 12, such counters may control the basic time
intervals associated with DDD, VVI, DVI, VDD, AAI, DDI, DDDR, VVIR,
DVIR, VDDR, AAIR, DDIR, CRT, and other modes of pacing.
[0057] Intervals defined by the timing and control module within
processor 80 may include atrial and ventricular pacing escape
intervals, refractory periods during which sensed P-waves and
R-waves are ineffective to restart timing of the escape intervals,
and the pulse widths of the pacing pulses. As another example, the
timing and control module may withhold sensing from one or more
channels of sensing module 86 for a time interval during and after
delivery of electrical stimulation to heart 12. The durations of
these intervals may be determined by processor 80 in response to
stored data in memory 82. The timing and control module of
processor 80 may also determine the amplitude of the cardiac pacing
pulses.
[0058] Interval counters implemented by the timing and control
module of processor 80 may be reset upon sensing of R-waves and
P-waves with detection channels of sensing module 86. In examples
in which IMD 16 provides pacing, signal generator 84 may include
pacer output circuits that are coupled, e.g., selectively by a
switching module, to any combination of electrodes 40, 42, 44, 46,
48, 50, 58, 62, or 66 appropriate for delivery of a bipolar or
unipolar pacing pulse to one of the chambers of heart 12. In such
examples, processor 80 may reset the interval counters upon the
generation of pacing pulses by signal generator 84, and thereby
control the basic timing of cardiac pacing functions, including
anti-tachyarrhythmia pacing.
[0059] The value of the count present in the interval counters when
reset by sensed R-waves and P-waves may be used by processor 80 to
measure the durations of R-R intervals, P-P intervals, P-R
intervals and R-P intervals, which are measurements that may be
stored in memory 82. Processor 80 may use the count in the interval
counters to detect a tachyarrhythmia event, such as atrial
fibrillation (AF), atrial tachycardia (AT), ventricular
fibrillation (VF), or ventricular tachycardia (VT). These intervals
may also be used to detect the overall heart rate, ventricular
contraction rate, and heart rate variability. A portion of memory
82 may be configured as a plurality of recirculating buffers,
capable of holding series of measured intervals, which may be
analyzed by processor 80 in response to the occurrence of a pace or
sense interrupt to determine whether the patient's heart 12 is
presently exhibiting atrial or ventricular tachyarrhythmia.
[0060] In some examples, an arrhythmia detection method may include
any suitable tachyarrhythmia detection algorithms. In one example,
processor 80 may utilize all or a subset of the rule-based
detection methods described in U.S. Pat. No. 5,545,186 to Olson et
al., entitled, "PRIORITIZED RULE BASED METHOD AND APPARATUS FOR
DIAGNOSIS AND TREATMENT OF ARRHYTHMIAS," which issued on Aug. 13,
1996, or in U.S. Pat. No. 5,755,736 to Gillberg et al., entitled,
"PRIORITIZED RULE BASED METHOD AND APPARATUS FOR DIAGNOSIS AND
TREATMENT OF ARRHYTHMIAS," which issued on May 26, 1998. U.S. Pat.
No. 5,545,186 to Olson et al. U.S. Pat. No. 5,755,736 to Gillberg
et al. is incorporated herein by reference in their entireties.
However, other arrhythmia detection methodologies may also be
employed by processor 80 in other examples.
[0061] In some examples, processor 80 may determine that
tachyarrhythmia has occurred by identification of shortened R-R (or
P-P) interval lengths. Generally, processor 80 detects tachycardia
when the interval length falls below 220 milliseconds (ms) and
fibrillation when the interval length falls below 180 ms. These
interval lengths are merely examples, and a user may define the
interval lengths as desired, which may then be stored within memory
82. This interval length may need to be detected for a certain
number of consecutive cycles, for a certain percentage of cycles
within a running window, or a running average for a certain number
of cardiac cycles, as examples.
[0062] In the event that processor 80 detects an atrial or
ventricular tachyarrhythmia based on signals from sensing module
86, and an anti-tachyarrhythmia pacing regimen is desired, timing
intervals for controlling the generation of anti-tachyarrhythmia
pacing therapies by signal generator 84 may be loaded by processor
80 into the timing and control module to control the operation of
the escape interval counters therein and to define refractory
periods during which detection of R-waves and P-waves is
ineffective to restart the escape interval counters for the an
anti-tachyarrhythmia pacing. Processor 80 detects data (e.g. data
observations etc.) at an IMD 16 check and/or interrogation time
point. Data is sensed based on signals from sensing module 86.
Additionally, cardioversion or defibrillation shock can be
determined to be needed based upon sensed data, and processor 80
may control the amplitude, form and timing of the shock delivered
by signal generator 84.
[0063] Memory 82 is configured to store data. Exemplary data can be
associated with a variety of operational parameters, therapy
parameters, sensed and detected data, and any other information
related to the therapy and treatment of patient 14. In the example
of FIG. 3, memory 82 also includes metric parameters 83 and metric
data 85. Metric parameters 83 may include all of the parameters and
instructions required by processor 80 and metric detection module
92 to sense and detect each of the patient metrics used to generate
the diagnostic information transmitted by IMD 16. Metric data 85
may store all of the data generated from the sensing and detecting
of each patient metric. In this manner, memory 82 stores a
plurality of automatically detected patient metrics as the data
required to generate a risk level of patient 14 being admitted to
the hospital due to heart failure.
[0064] Metric parameters 83 may include definitions of each of the
patient metrics automatically sensed or measured by metric
detection module 92. These definitions may include instructions
regarding what electrodes or sensors to use in the detection of
each metric. Preferred metrics include an (1) impedance trend index
(also referred to as OPTIVOL.RTM. commercially available in IMDs
from Medtronic Inc., located in MN), (2) intrathoracic impedance,
(3) atrial tachycardia/atrial fibrillation (AT/AF) burden, (4) mean
ventricular rate during AT/AF, (5) patient activity, (6) V rate,
(7) day and night heart rate, (8) percent CRT pacing, and/or (9)
number of shocks. Impedance trend index is described with respect
to U.S. pat. Ser. No. 10/727,008 filed on Dec. 3, 2003 issued as
U.S. Pat. No. 7,986,994, and assigned to the assignee of the
present invention, the disclosure of which is incorporated by
reference in its entirety herein. Other suitable metrics can also
be used. For example, a reference or baseline level impedance is
established for a patient from which subsequently acquired raw
impedance data is compared. For example, raw impedance can be
acquired from the electrodes (e.g. RV coil to Can) and compared to
the reference impedance. Baseline impedance can be derived by
averaging impedance over a duration of 7 days (1-week) to 90 days
(3-months).
[0065] Metric parameters 83 may also store a metric-specific
threshold for each of the patient metrics automatically detected by
metric detection module 92. Metric thresholds may be predetermined
and held constant over the entire monitoring of patient 14. In some
examples, however, metric thresholds may be modified by a user
during therapy or processor 80 may automatically modify one or more
metric thresholds to compensate for certain patient conditions. For
example, a heart rate threshold may be changed over the course of
monitoring if the normal or baseline heart rate has changed during
therapy.
[0066] In one example, these metric-specific thresholds may include
a thoracic fluid index threshold of about 60 .quadrature.-days an
atrial fibrillation burden threshold of approximately 6 consecutive
hours, a ventricular contraction rate threshold approximately equal
to 90 beats per minute for 24 hours, a patient activity threshold
approximately equal to 1 hour per day for seven consecutive days, a
nighttime heart rate threshold of approximately 85 beats per minute
for seven consecutive days, a heart rate variability threshold of
approximately 40 milliseconds for seven consecutive days, a cardiac
resynchronization therapy percentage threshold of 90 percent for
five of seven consecutive days, and an electrical shock number
threshold of 1 electrical shock. These thresholds may be different
in other examples, and may be configured by a user, e.g., a
clinician, for an individual patient.
[0067] Processor 80 may alter the method with which patient metrics
are stored in memory 82 as metric data 85. In other words,
processor 80 may store the automatically detected patient metrics
with a dynamic data storage rate.
[0068] Metric data 85 is a portion of memory 82 that may store some
or all of the patient metric data that is sensed and/or detected by
metric detection module 92. Metric data 85 may store the data for
each metric on a rolling basis during an evaluation window. The
evaluation window may only retain recent data and delete older data
from the evaluation window when new data enters the evaluation
window. In this manner, the evaluation window may include only
recent data for a predetermined period of time. In one or more
other embodiments, memory can be configured for long term storage
of data. Processor 80 may access metric data when necessary to
retrieve and transmit patient metric data and/or generate heart
failure risk levels. In addition, metric data 85 may store any and
all data observations, heart failure risk levels or other generated
information related to the heart failure risk of patient 14. The
data stored in metric data 85 may be transmitted as part of
diagnostic information. Although metric parameters 83 and/or metric
data 85 may consist of separate physical memories, these components
may simply be an allocated portion of the greater memory 82.
[0069] Metric detection module 92 may automatically sense and
detect each of the patient metrics. Metric detection module 92 may
then generate diagnostic data, e.g., data that indicates a
threshold has been crossed, risk levels, based on the patient
metrics. For example, metric detection module 92 may measure the
thoracic impedance, analyze an electrogram of heart 12, monitor the
electrical stimulation therapy delivered to patient 14, or sense
the patient activity. It is noted that functions attributed to
metric detection module 92 herein may be embodied as software,
firmware, hardware or any combination thereof. In some examples,
metric detection module 92 may at least partially be a software
process executed by processor 80. Metric detection module 92 may
sense or detect any of the patient metrics used as a basis for
generating the heart failure risk level or otherwise indication of
heart failure status or that patient 14 is at risk for worsening
HF. In one example, metric detection module 92 may compare each of
the patient metrics to their respective metric-specific thresholds
defined in metric parameters 83 to generate the heart failure risk
level. Metric detection module 92 may automatically detect two or
more patient metrics. In other examples, metric detection module 92
may detect different patient metrics.
[0070] In one example, metric detection module 92 may analyze
electrograms received from sensing module 86 to detect an atrial
fibrillation or atrial tachycardia, and determine atrial
tachycardia or fibrillation burden, e.g., duration, as well as a
ventricular contraction rate during atrial fibrillation. Metric
detection module 92 may also analyze electrograms in conjunction
with a real-time clock, patient posture or activity signal, e.g.,
from activity sensor 96, and/or other physiological signals
indicative of when a patient is asleep or awake to determine a
nighttime (or sleeping) heart rate or a daytime (or awake) heart
rate or a difference between the day and night heart rate, and also
analyze electrograms to determine a heart rate variability, or any
other detectable cardiac events from one or more electrograms. As
described above, metric detection module 92 may use peak detection,
interval detection, or other methods to analyze the
electrograms.
[0071] In addition, metric detection module 92 may include and/or
control impedance module 94 and activity sensor 96. Impedance
module 94 may be used to detect the thoracic impedance used to
generate the thoracic fluid index. As described herein, impedance
module 94 may utilize any of the electrodes of disclosed herein to
take intrathoracic impedance measurements. In other examples,
impedance module 94 may utilize separate electrodes coupled to IMD
16 or in wireless communication with telemetry module 88. Once
impedance module 94 measures the intrathoracic impedance of patient
14, metric detection module 92 may generate the thoracic fluid
index and compare the index to the thoracic fluid index threshold
defined in metric parameters 83.
[0072] Activity sensor 96 may include one or more accelerometers or
other devices capable of detecting motion and/or position of
patient 14. Activity sensor 96 may therefore detect activities of
patient 14 or postures engaged by patient 14. Metric detection
module 92 may, for example, monitor the patient activity metric
based on the magnitude or duration of each activity and compare the
determined metric data to the activity threshold defined in metric
parameters 83. In addition to detecting events of patient 14,
metric detection module 92 may also detect certain therapies
delivered by signal generator 84, e.g., as directed by processor
80. Metric detection module 92 may monitor signals through signal
generator 84 or receive therapy information directly from processor
80 for the detection. Example patient metrics detected by this
method may include a cardiac resynchronization therapy percentage
or metrics related to delivery of electrical shocks.
[0073] The cardiac resynchronization therapy (CRT) metric may be
the amount or percentage of time each day, or an amount of
percentage of cardiac cycles, as examples, that IMD 16 delivers
cardiac resynchronization therapy to heart 12. Low CRT amounts or
percentages may indicate that beneficial therapy is not being
effectively delivered and that adjustment of therapy parameters,
e.g., an atrioventricular delay or a lower pacing rate, may improve
therapy efficacy. In one example, higher CRT amounts or percentages
may indicate that heart 12 is sufficiently pumping blood through
the vasculature with the aid of therapy to prevent fluid buildup.
In examples of other types of cardiac pacing (non-CRT) or
stimulation therapy, higher therapy percentages may indicate that
heart 12 is unable to keep up with blood flow requirements. In one
or more other embodiments, low effective CRT amounts or effective
V-pacing for CRT pacing can also be used as indicators of improved
therapy efficacy.
[0074] An electrical shock may be a defibrillation event or other
high energy shock used to return heart 12 to a normal rhythm. The
metric related electrical shocks may be a number or frequency of
electrical shocks, e.g., a number of shocks within a period of
time. Metric detection module 92 may detect these patient metrics
as well and compare them to a cardiac resynchronization therapy
percentage and shock event threshold, respectively, defined in
metric parameters 83 to determine when each patient metric has
become critical. In one example, the electrical shock event metric
may become critical when a threshold number of shocks is delivered,
e.g., within a time period, or even when patient 14 even receives
one therapeutic shock.
[0075] Metric detection module 92 may include additional
sub-modules or sub-routines that detect and monitor other patient
metrics used to monitor patient 14 and/or generate the HF risk
level. In some examples, metric detection module 92, or portions
thereof, may be incorporated into processor 80 or sensing module
86. In other examples, raw data used to produce patient metric data
may be stored in metric data 85 for later processing or
transmission to an external device. An external device may then
produce each patient metric from the raw data, e.g., electrogram or
raw intrathoracic impedance which is subsequently compared to a
reference impedance. In other examples, metric detection module 92
may additionally receive data from one or more implanted or
external devices used to detect each metric which IMD 16 may store
as metric data.
[0076] In some examples, the patient metric thresholds used to
generate the risk levels may change over time, e.g., the patient
metric thresholds may either be modified by a user or automatically
changed based on other patient conditions. Telemetry module 88 may
receive commands from programmer 24, for example, to modify one or
more metric parameters 83 (e.g., metric creation instructions or
metric-specific thresholds). In some examples, processor 80 may
automatically adjust a metric-specific threshold if certain
conditions are present in patient 14. For example, the threshold
may be adjusted if patient 14 is experiencing certain arrhythmias
or data contained in cardiac electrograms change, e.g., there is a
deviation in ST elevations or presence of pre-ventricular
contractions, in such a manner that requires a change in the
threshold.
[0077] Processor 80 may generate risk levels (e.g. risk of, or
exhibiting hypervolemia, hypovolemia, HFH risk level) based upon
the patient metrics sensed, detected, and stored in metric data 85
of memory 82. For example, processor 80 may continually update the
risk level as metric detection module 92 updates each patient
metric. In other examples, processor 80 may periodically update the
HFH risk level according to an updating schedule. In one or more
other embodiments, the total number of data observations that
exceed or cross a threshold within a pre-specified period of time
can be used to determine the risk of a heart failure event or
worsening HF.
[0078] As described above, processor 80 may provide an alert to a
user, e.g., of programmer 24, regarding the data from any patient
metric and/or the HFH risk level. In one example, processor 80 may
provide an alert with the HFH risk level when programmer 24 or
another device communicates with IMD 16. Telemetry module 88
includes any suitable hardware, firmware, software or any
combination thereof for communicating with another device, such as
programmer 24 (FIG. 1). Under the control of processor 80,
telemetry module 88 may receive downlink telemetry from and send
uplink telemetry to programmer 24 with the aid of an antenna, which
may be internal and/or external. Processor 80 may provide the data
to be uplinked to programmer 24 and the control signals for the
telemetry circuit within telemetry module 88, e.g., via an
address/data bus. In some examples, telemetry module 88 may provide
received data to processor 80 via a multiplexer.
[0079] In some examples, processor 80 may transmit atrial and
ventricular heart signals, e.g., EGMs, produced by atrial and
ventricular sense amplifier circuits within sensing module 86 to
programmer 24. Programmer 24 may interrogate IMD 16 to receive the
heart signals. Processor 80 may store heart signals within memory
82, and retrieve stored heart signals from memory 82. Processor 80
may also generate and store marker codes indicative of different
cardiac events that sensing module 86 detects, and transmit the
marker codes to programmer 24. An example pacemaker with
marker-channel capability is described in U.S. Pat. No. 4,374,382
to Markowitz, entitled, "MARKER CHANNEL TELEMETRY SYSTEM FOR A
MEDICAL DEVICE," which issued on Feb. 15, 1983 and is incorporated
herein by reference in its entirety.
[0080] In some examples, IMD 16 may signal programmer 24 to further
communicate with and pass the alert through a network such as the
Medtronic CareLink.RTM. Network developed by Medtronic, Plc. of
Minneapolis, MN, or some other network linking patient 14 to a
clinician. In this manner, a computing device or user interface of
the network may be the external computing device that delivers the
alert, e.g., patient metric data. In other examples, one or more
steps in the generation of the heart failure risk level may occur
within a device external of patient 14, e.g., within programmer 24
or a server networked to programmer 24. In this manner, IMD 16 may
detect and store patient metrics before transmitting the patient
metrics to a different computing device.
[0081] System 100 controls implementation of an intervention method
200, depicted in a flow diagram of FIG. 4, to seamlessly adjust
patient's therapy (e.g. medication). At block 202, a determination
is made as to whether the patient is experiencing increased risk of
worsening HF condition. Risk of worsening HF condition is
calculated using data such as data acquired from IMD 16. For
example, data, acquired from the IMD 16, shows a threshold level is
crossed. The data, showing an exceedance or that a threshold has
been crossed, is transmitted to server 130. Other data that may be
useful for determining risk of worsening condition can be obtained
from computing devices 102a-n.
[0082] Server 130 combines all of the diagnostic data in order to
determine a patient's HF risk. Numerous methods exist for
determining a patient's risk of experiencing a HF event. One
methodology uses a Bayesian Belief Probabilistic model to
categorize patients into three risk categories--low, medium and
high. Exemplary medium and high risk calculations are shown and
described in US2012032243, entitled HEART FAILURE MONITORING AND
NOTIFICATION and assigned to the assignee of the present invention,
the disclosure of which is incorporated by reference in its
entirety herein. One or more other embodiments that may be employed
is directed to Martin R. Cowie et al., Development and Validation
Of An Integrated Diagnostic Algorithm Derived From Parameters
Monitored in Implantable Devices For Identifying Patients At Risk
For Heart Failure Hospitalization In An Ambulatory Setting,
European Heart Journal (2013) 34, 2472-2480
doi:10.1093/eurheartj/eht083, the disclosure of which is
incorporated by reference in its entirety herein.
[0083] Briefly, the present disclosure uses a set of variables as
input. Exemplary set of variables include thoracic impedance,
activity, heart rate variability, heart rate, and a combination
variable based on arrhythmia and shock related information
collected by the IMD 16. Intrathoracic impedance (e.g.
OptiVol.RTM.) is a useful measure of a patient's HF status because
HF status typically worsens when atrial filling pressure increases
thereby causing retention of fluid in the pulmonary circulation. If
sustained over time, fluid can infiltrate into interstitial space
leading to worsening pulmonary congestion. Since blood and
interstitial fluid are highly conductive, fluid accumulation in the
pulmonary system leads to a reduction in thoracic impedance.
[0084] After a HF risk status of the patient is calculated, the HF
risk status data is then stored into memory 136 of the server 130.
If a patient's risk is deemed high, the patient automatically falls
within the scope of worsening condition. Worsening HF condition
also occurs in medium risk patients who exhibit sign/symptoms
present (e.g. weight gain, dyspnea etc.) that may be acquired from
external biometric data devices.
[0085] After evaluating patient information, a determination can be
made that the risk alert from the patient is not specific to
worsening HF. In this scenario, the NO path from block 202
continues from block 206 in which the method 200 is terminated and
the process returns to monitoring for worsening HF conditions in
the patient. The YES path continues from block 202 to block 204 in
which medical personnel (e.g. nurse located a central communication
center etc.) communicates with the patient through electronic
communication (e.g. email, text messaging, phone call or mail) in
order to determine whether the patient's worsening condition is HF
related. The medical personnel may present one or more questions to
the patient. For example, the patient may be asked if he or she had
undergone a recent surgery. At block 208, a determination is made
as to whether the threshold crossing is related to HF. A threshold
crossing can be confirmed as a HF occurrence based upon information
provided by the patient. Typically, to confirm whether the
worsening condition is HF related, the patient is asked to respond
to the questions presented below. The questions can be posed by a
nurse located near the central server 130 or electronically
presented to the patient via server 130 to a GUI associated with a
computing device 102a-n. Exemplary questions that can be posed to a
patient include the following:
[0086] 1. Has the CRT-D device or lead been changed?
[0087] 2. Has the patient been discharged from the hospital within
the last two days?
[0088] 3. Did the patient receive intravenous fluids for more than
1 day while in the hospital?
[0089] 4. Did the patient experience chills, shivering, shaking or
muscle aches?
[0090] 5. Has the patient been treated for a chronic obstructive
pulmonary disease (COPD) exacerbation?
[0091] 6. Did any changes occur to baseline diuretic medication in
the past 3 weeks?
[0092] If the response to anyone of the questions is "yes", the
threshold crossing is deemed to not be a HF occurrence. All other
occurrences may be deemed HF related.
[0093] If a threshold has been confirmed as having been crossed,
the YES path continues to block 210 in which a determination
associated with blood pressure (BP) will require system 100 to
intervene by electronically indicating that medication should be
administered to the patient. BP of the patient can be measured
relative to a systolic threshold level (TS) and/or a diastolic
threshold level (TD). TD and/or TS can be the typical normal
threshold levels or can be individually established for each
patient. A determination is made as to whether BP<TS. If BP is
greater than TS, then the NO path continues to block 206 and the
method 200 is terminated and the process returns to monitoring for
worsening HF conditions in the patient. In contrast, if BP is
greater than or equal to TS, then the NO path from block 210 to
block 212 causes a first round of medication to be provided to the
patient. Administration of a diuretic helps to eliminate water and
may reduce blood pressure. To obtain the medication, server 130 is
configured to automatically transmit a pre-authorized prescription
to the patient. Alternatively, the centralized communication center
staffed by a registered nurse contacts the patient to indicate that
the medication at a certain dosage should be taken. The prescribed
medication is stored in the home of the patient for easy access.
The patient then starts taking the prescribed medication. In one
embodiment, the medication is a diuretic medication (e.g.
furosemide) or vasodilator (e.g. nitrate). Diuretics typically
eliminate water from the patient and reduce the blood pressure.
[0094] Another determination is made at block 210 as to whether
BP<TD. If BP is less than or equal to TD, then the YES path
continues to block 206 and the process stops and returns to
monitoring for worsening HF conditions in the patient. In contrast,
if BP is greater than TD, then the NO path from block 210 to block
212 causes a first round of medication to be provided to the
patient, as described above.
[0095] At block 214, a determination is made as to whether the
patient is experiencing hypotension or extreme weight gain in a
short period of time. If the patient is experiencing hypotension,
the YES path continues to block 224 in which another determination
is made as to whether the patient is experiencing HF symptoms. The
YES path from block 224 continues to block 226 that causes the
medication to be stopped or terminated. Medication can be stopped
for a variety of conditions. Exemplary conditions include the
following:
[0096] If the patient weighs less than 150 pounds, and the
patient's weight changes by 3 pounds per 2 days.
[0097] If the patient weighs between 151-300 pounds, and the
patient's weight changes by 4 pounds per 2 days.
[0098] if the patient weighs greater than 301 pounds, and the
patient's weight changes by 5 pounds per 2 days.
[0099] One condition requires both a BP condition and the presence
of a symptom, as listed immediately below. The BP condition
requires the patient exhibit either a systolic blood pressure of
the patient is less than 85 mmHg or a diastolic pressure of less
than 40 mm Hg. In addition to meeting one of the BP conditions, the
patient must be experiencing a symptom that has been conveyed to
medical personnel.
[0100] Exemplary symptoms include (1) recent lightheadedness when
moving from sitting to standing positions, or (2) muscle cramping.
In addition or alternatively, the physician may customize any one
of these conditions to a patient by adding or reducing the weight
gain amount or blood pressure level.
[0101] The NO path from blocks 214 and 224 continue to block 216 in
which a determination is made as to whether the patient has
recovered from his or her worsening HF condition. Exemplary
criteria for evaluating PRN efficacy in medication intervention is
shown in FIG. 6. Recovery criterion is computed by the server 130
to evaluate PRN efficacy using raw intrathoracic impedance,
acquired from IMD 16 associated with the patient, since impedance
responds dynamically to patient volume status. Computation of
recovery criterion requires the difference to be calculated between
raw intrathoracic impedance and the reference impedance. Reference
impedance is a component of impedance trend. Daily values for both
raw and reference impedance are included with all device diagnostic
transmissions spanning a duration of up to 14 months. The
difference between raw and reference impedances on pre-specified
time period (e.g. four day time period etc.) is required to compute
recovery criterion (RC)--the day of PRN initiation (x.sub.0),
evaluation day (x.sub.3), evaluation Day 1 (x.sub.2), and
evaluation Day 2 (x.sub.1), recovery criterion is then computed
according to the following equation:
RC=100*(x.sub.0-xa)
(+x.sub.0-x.sub.2)+(x.sub.0-x.sub.3))/x.sub.0.
[0102] If the value of RC is greater than a threshold value of 70
(i.e. cumulative impedance recovery over the last 3 days is 70% or
more from Day 0 of receiving the initial transmission), the
intervention is deemed to be successful. If the value of RC is less
than or equal to 70, the intervention is deemed unsuccessful and
appropriate follow-up action (i.e. second PRN or notification to
the investigator) is taken.
[0103] If it is determined at block 216 that the patient has
recovered from his worsening HF condition, the YES path continues
from block 216 to block 220 in which the patient's status of
recovery is stored into memory of server 130. The process is
stopped at block 206 and monitoring for worsening HF condition
continues. If the patient is not experiencing a recovery, the NO
path from block 216 to block 218 requires a patient's blood
pressure to be checked and a second round of medication to be
initiated. Typically, no additional round of medication is made
beyond the second round of medication. Alternatively, a physician
prescribed number N can be set of rounds medication can be
administrated where N is any number from 1 to 10.
[0104] At block 218, another determination is made as to whether
the patient is experiencing hypotension or extreme weight gain. The
YES path continues from block 222 to block 224, as previously
described. The NO path from block 222 to block 228 in which the
recovery criteria, described relative to block 216, is repeated.
The YES path from block 228 continues to block 230 in which the
patient's status of recovery is stored into memory of server 130.
The process is stopped 206 and monitoring continues for worsening
HF condition.
[0105] The NO path from 228 to block 232 requires that the patient
be contacted by medical personnel (e.g. nurse) so that a blood
sample can be taken for evaluation and confirmation that the proper
dosage of medication was provided. Block 240 also requires a blood
sample be taken for evaluation and confirmation that the proper
dosage of medication was provided.
[0106] At block 234, a determination is made as to whether criteria
for baseline medications are met. The YES path from block 234 to
block 238 requires the health clinic to evaluate and change the
baseline medication, if necessary. Exemplary baseline medications
along with information that may be useful for medical personnel are
presented below.
[0107] If changes to PRN medications are made by a physician, an
updated prescription form must be electronically modified in the
system 100 and records stored into memory. For example, the updated
prescription by the physician can be sent (i.e. faxed, emailed) to
system 100, which will automatically update the therapy.
[0108] Method 200 is stopped at block 236.
Exemplary Embodiments of the Disclosure
[0109] The following embodiments are enumerated consecutively from
1 to 28 provide for various aspects of the present disclosure. In
one embodiment, in a first (1) paragraph the present disclosure
provides a method for determining whether to intervene with a
patient's treatment, the method comprising:
[0110] (a) sensing data through an implanted sensor;
[0111] (b) using an implanted processor to measure the data against
a threshold stored in a memory of an implanted device to determine
whether the data is considered to be an HF worsening episode
occurrence;
[0112] (c) storing the occurrence in the memory of the implanted
device;
[0113] (d) transmitting the occurrence to an external device;
[0114] (e) determining risk status from the occurrence and any
other applicable data using the external device;
[0115] (f) acquiring additional data from one or more other
external devices, the additional data being one of weight,
symptoms, and blood pressure; and
[0116] (g) using the external device to determine whether to adjust
treatment of the patient in response to the risk status, the data
acquired from the implanted device memory and the one or more other
external devices.
A second embodiment is the method according to paragraph 1 further
comprising:
[0117] storing a treatment plan into the external device's memory,
the treatment plan comprising a first round of medication, a second
round of medication and/or up to N rounds in which N is any
integer.
A third embodiment according to any embodiments 1-2 wherein the
treatment plan comprises delivery of a prescribed medication, the
prescribed medication adjusted without directly communicating with
the patient's physician any time after storing the treatment plan.
A fourth embodiment according to any embodiments of 1-3, further
comprising:
[0118] displaying the adjusted treatment on a graphical user
interface in response to determining that treatment requires
adjustment.
A fifth embodiment according to any embodiments of 1-4 further
comprising: acquiring raw impedance data after a prescribed period
of time in response to adjusting the treatment of the patient; and
using the raw impedance data to determine whether the patient is
improving in response to the treatment. Optionally, raw impedance
can be used to determine whether the patient is recovering or has
recovered. A sixth embodiment according to any embodiments of 1-5
further comprising: determining whether the raw impedance data,
acquired from the implanted device memory, crosses a threshold; in
response to determining whether the raw impedance data crosses the
threshold, determining whether the raw impedance data is considered
a heart failure exacerbation. Optionally, HF exacerbation can mean
a treatable HF event. A seventh embodiment according to any
embodiments of 1-6, wherein the raw impedance data that is a
non-heart failure exacerbation does not require an intervention by
the healthcare system. A eighth embodiment according to any
embodiments of 1-7, wherein the non-heart failure exacerbation does
not cause an adjustment to treatment. A ninth embodiment according
to any embodiments of 1-8, wherein the non-heart failure
exacerbation triggers a notification to medical personnel. A tenth
embodiment according to any embodiments of 1-9, wherein the
non-heart failure exacerbation does not trigger an intervention. An
eleventh embodiment according to any embodiments of 1-10, wherein
the raw impedance data that is a heart failure exacerbation that
requires an intervention by the healthcare system. A twelfth
embodiment according to any embodiments of 1-11 further
comprising:
[0119] determining whether to terminate adjusted treatment in
response to data monitored after treatment was adjusted.
A thirteenth embodiment according to any embodiments of 1-12,
wherein termination of adjusted treatment is based upon one of
patient blood pressure, and/or symptoms. A fourteenth embodiment
according to any embodiments of 1-13 further comprising: generating
a notification for delivery of a first round of medication. A
fifteenth embodiment according to any embodiments of 1-14, further
comprising: generating a notification for delivery of a second
round of medication. A sixteenth embodiment according to any
embodiments of 1-15, further comprising: monitoring one of the
implanted device memory data and the external device data after
delivery of one of a first or a second round of medication. A
seventeenth embodiment according to according to any embodiments of
1-16, further comprising: generating a notification to one of
medical personnel and a patient for a blood sample to be acquired
and tested. A eighteenth embodiment according to any embodiments of
1-17 further comprising: adjusting therapy in response determining
weight loss. A nineteenth embodiment according to any embodiments
of 1-17 further comprising: adjusting therapy in response
determining blood pressure and/or a symptom. A twentieth embodiment
according to any embodiments of 1-19 wherein the symptom related to
one of lightheadedness and muscle cramping. A twenty first
embodiment according to any embodiments of 1-20 wherein the
adjusted therapy involves cessation of one or more medications. A
twenty second embodiment according to any of embodiments 1-21
wherein the adjusted therapy involves one or more medications being
increased in dosage. A twenty third embodiment according to any
embodiments of 1-22 wherein one or more baseline medications are
examined. A twenty fourth embodiment according to any embodiments
of 1-23 further comprising: determining whether one of a set
criteria has been met; and triggering review of one or more
baseline medications in response to determining whether one of a
set criteria has been met. A twenty fifth embodiment according to
any embodiments of 1-24 wherein the one of the set criteria
comprises: (a) average pre-specified time period impedance is less
a threshold; (b) two or more medication interventions occurred
within a pre-specified amount of time; and (c) two or more
medication interventions were administered to the patient. A twenty
sixth embodiment according to any embodiments of 1-25 wherein the
threshold for the average pre-specified time period impedance is
less than or about less than 66 Ohms. A twenty seventh embodiment
according to any embodiments of 1-26 wherein the pre-specified time
period is about three months. A twenty eighth embodiment wherein
the treatment plan comprises medication as a transient increase in
diuretic or vasodilator. Transient increase in medication means
that a nominal amount of diuretic or vasodilator can be made
without approval from a physician.
[0120] A twenty eighth embodiment involving a method for
determining whether to intervene with a patient's treatment, the
method comprising:
[0121] (a) sensing data through an implanted sensor;
[0122] (b) using an implanted processor of an implanted device to
measure the data against a threshold stored in a memory of the
implanted device to determine whether the data is considered to be
a HF worsening episode occurrence;
[0123] (c) storing the occurrence in the memory of the implanted
device;
[0124] (d) transmitting from the implanted device the occurrence to
an external device;
[0125] (e) using the external device to determine the risk status
from the occurrence and any other applicable data;
[0126] (f) acquiring additional data, by the external device, from
one or more other external devices, the additional data being one
of weight, symptoms, and blood pressure; and
[0127] (g) using the external device to determine whether to adjust
the patient's treatment in response to the risk status, the data
acquired from the implanted device memory and the one or more other
external devices.
[0128] A twenty ninth embodiment of a system for determining
whether to intervene with a patient's treatment, the system
comprising:
[0129] an implantable device having a memory;
[0130] an implantable sensor;
[0131] an implantable processor;
[0132] an external device;
[0133] sensing means for sensing data through the implanted
sensor;
[0134] the implanted processor configured to compare the data
against a threshold stored in the memory of the implanted device to
determine whether the data is considered to be indicative of a
heart failure (HF) worsening episode occurrence based on a result
of the comparison;
[0135] storing means for storing a determined occurrence in the
memory of the implanted device;
[0136] transmitting means for transmitting the occurrence to the
external device;
[0137] processing means for determining a risk status from the
occurrence and any other applicable data using the external
device;
[0138] means for acquiring additional data, the additional data
being one of weight, symptoms, and blood pressure; and
[0139] the external device configured to determine whether to
adjust the patient's treatment based on the risk status, the data
acquired from the implanted device memory and the one or more other
external devices.
[0140] A thirtieth embodiment of a system of embodiment 29 wherein
the additional data is acquired from the external device or one or
more other external devices.
[0141] A thirty first embodiment of a system of embodiment 29 or 30
wherein the additional data related to the blood pressure is
acquired from the implantable processor, another implantable
processor associated with another implantable device, and a
wireless pulmonary artery sensor. An example of such a wireless
pulmonary artery sensor located in the pulmonary artery is found in
U.S. patent application Ser. No. 15/378,989, filed Dec. 14, 2016,
and assigned to the assignee of the present invention, the
disclosure of which is incorporated by reference in its entirety
herein. The wireless pulmonary artery sensor is configured to
wirelessly communicate with other implantable medical devices for
monitoring and/or storing sensed physiological data such as
LINQ.TM.. LINQ.TM. can then wirelessly communicate data to an
external device such as a portable device (e.g. iPhone, computer)
or to the external device such as server 130. Tissue conductance
communication is used to communicate between the wireless pulmonary
artery sensor and LINQ.TM.. An exemplary implantable monitoring
device is found in US Patent Publication No. US 2016-0310031 A1,
filed Apr. 20, 2016 to Sarkar, and assigned to the assignee of the
present invention, the disclosure of which is incorporated by
reference in its entirety herein
[0142] A thirty second embodiment of a system according to one of
embodiments 29-31 wherein the additional data related to the blood
pressure is acquired from the external device or one or more
external devices.
[0143] A thirty second embodiment of a system according to one of
embodiments 29-32 wherein the implanted sensor is mechanically and
electrically connected to the implanted device.
[0144] A thirty third embodiment of a system according to one of
embodiments 29-33 wherein the implanted sensor is not mechanically
connected to the implanted device.
[0145] A thirty fourth embodiment of a system according to one of
embodiments 29-34 further comprising:
[0146] storing means for storing a treatment plan into a memory of
the external device, the treatment plan comprising a first round of
medication and a second round of medication.
[0147] A thirty fifth embodiment of a system according to one of
embodiments 29-34 wherein the treatment plan comprises delivery of
a prescribed medication, the prescribed medication adjusted without
directly communicating with the patient's physician any time after
storing the treatment plan into memory.
[0148] A thirty sixth embodiment of a system according to one of
embodiments 29-35, further comprising:
[0149] displaying means for displaying the adjusted treatment on a
graphical user interface in response to determining that the
patient's treatment requires adjustment.
[0150] A thirty seventh embodiment of a system according to one of
embodiments 29-36 further comprising:
[0151] means for acquiring raw impedance data after a prescribed
period of time in response to adjusting the treatment of the
patient; and
[0152] means for using the raw impedance data to determine whether
the patient is improving in response to the treatment.
[0153] A thirty eighth embodiment of a system according to one of
embodiments 29-37, further comprising:
[0154] processing means for determining whether the raw impedance
data, acquired from the implanted device memory, crosses a
threshold; and
[0155] in response to determining whether the raw impedance data
crosses the threshold, determining whether the raw impedance data
is considered a heart failure exacerbation.
[0156] A thirty ninth embodiment of a system according to one of
embodiments 29-38, wherein the raw impedance data that is a
non-heart failure exacerbation does not require an intervention by
the healthcare system.
[0157] A fortieth embodiment of a system according to one of
embodiments 29-39, wherein the non-heart failure exacerbation does
not cause an adjustment to treatment.
[0158] A forty first embodiment of a system according to one of
embodiments 29-40, wherein the non-heart failure exacerbation
triggers a notification to medical personnel.
[0159] A forty second embodiment of a system according to one of
embodiments 29-41, wherein the non-heart failure exacerbation does
not trigger an intervention.
[0160] A forty third embodiment of a system according to one of
embodiments 29-42, wherein the raw impedance data that is a heart
failure exacerbation that requires an intervention by the
healthcare system.
[0161] A forty fourth embodiment of a system according to one of
embodiments 29-43, further comprising: processing means for
determining whether to terminate adjusted treatment in response to
data monitored after treatment was adjusted.
[0162] A forty fifth embodiment of a system according to one of
embodiments 29-44, wherein termination of adjusted treatment is
based upon one of patient blood pressure, and symptoms. The
external device may be a server 130. Another external device may be
another computer or server.
[0163] This disclosure has been provided with reference to
illustrative embodiments and is not meant to be construed in a
limiting sense. As described previously, one skilled in the art
will recognize that other various illustrative applications may use
the techniques as described herein to take advantage of the
beneficial characteristics of the apparatus and methods described
herein. Various modifications of the illustrative embodiments, as
well as additional embodiments of the disclosure, will be apparent
upon reference to this description.
* * * * *