U.S. patent application number 15/969369 was filed with the patent office on 2019-11-07 for sensing for heart failure management.
The applicant listed for this patent is Medtronic, Inc.. Invention is credited to Tommy D. Bennett, James K. Carney, Jonathan L. Kuhn, Shantanu Sarkar, Vinod Sharma, Todd M. Zielinski.
Application Number | 20190336076 15/969369 |
Document ID | / |
Family ID | 66542541 |
Filed Date | 2019-11-07 |
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United States Patent
Application |
20190336076 |
Kind Code |
A1 |
Kuhn; Jonathan L. ; et
al. |
November 7, 2019 |
SENSING FOR HEART FAILURE MANAGEMENT
Abstract
In some examples, determining a heart failure status includes
using an implantable medical device configured for subcutaneous
implantation and comprising a plurality of electrodes and an
optical sensor. Processing circuitry of a system comprising the
device may determine, for a patient, a current tissue oxygen
saturation value based on a signal received from the at least one
optical sensor, a current tissue impedance value based on a
subcutaneous tissue impedance signal received from the electrodes,
and a current pulse transit time value based on a cardiac
electrogram signal received from the electrodes and at least one of
the signal received from the optical sensor and the subcutaneous
tissue impedance signal. The processing circuitry may further
compare the current tissue oxygen saturation value, current tissue
impedance value, and current pulse transit time value to
corresponding baseline values, and determine the heart failure
status of the patient based on the comparison.
Inventors: |
Kuhn; Jonathan L.; (Ham
Lake, MN) ; Carney; James K.; (Roseville, MN)
; Sharma; Vinod; (Maple Grove, MN) ; Sarkar;
Shantanu; (Roseville, MN) ; Zielinski; Todd M.;
(Ham Lake, MN) ; Bennett; Tommy D.; (Shoreview,
MN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Medtronic, Inc. |
Minneapolis |
MN |
US |
|
|
Family ID: |
66542541 |
Appl. No.: |
15/969369 |
Filed: |
May 2, 2018 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 5/02405 20130101;
A61B 5/1459 20130101; A61B 5/7282 20130101; A61N 1/3756 20130101;
A61B 5/486 20130101; G16H 40/63 20180101; A61B 5/076 20130101; A61B
5/7275 20130101; A61N 1/3956 20130101; A61B 5/686 20130101; A61B
5/0261 20130101; A61B 5/0538 20130101; A61B 5/0059 20130101; A61N
1/362 20130101; A61B 5/14552 20130101; A61B 5/0205 20130101; A61B
5/0422 20130101; A61B 5/02125 20130101 |
International
Class: |
A61B 5/00 20060101
A61B005/00; A61B 5/0205 20060101 A61B005/0205; A61B 5/042 20060101
A61B005/042; A61B 5/07 20060101 A61B005/07; A61B 5/1455 20060101
A61B005/1455; A61B 5/1459 20060101 A61B005/1459 |
Claims
1. A method for determining a heart failure status of a patient
using an implantable medical device configured for subcutaneous
implantation outside of a thorax of the patient, the implantable
medical device comprising a plurality of electrodes and at least
one optical sensor, the method comprising, by processing circuitry
of a medical device system comprising the implantable medical
device: determining a current tissue oxygen saturation value of the
patient based on a signal received from the at least one optical
sensor; determining a current tissue impedance value of the patient
based on a subcutaneous tissue impedance signal received from a
first at least two of the plurality of electrodes; determining a
current pulse transit time value of the patient based on a cardiac
electrogram signal received from a second at least two of the
plurality of electrodes and at least one of the signal received
from the at least one optical sensor and the subcutaneous tissue
impedance signal; comparing the current tissue oxygen saturation
value, the current tissue impedance value, and the current pulse
transit time value to corresponding ones of a baseline tissue
oxygenation saturation value, a baseline tissue impedance value,
and a baseline pulse transit time value; and determining the heart
failure status of the patient based on the comparison.
2. The method of claim 1, wherein comparing the current tissue
oxygen saturation value, the current tissue impedance value, and
the current pulse transit time value to the corresponding ones of
the baseline tissue oxygenation saturation value, the baseline
tissue impedance value, and the baseline pulse transit time value
comprises: determining whether a difference between the current
tissue oxygen saturation value and the baseline tissue oxygen
saturation value satisfies a tissue oxygen saturation threshold
value that is associated with a change in a tissue perfusion status
of the patient; determining whether a difference between the
current tissue impedance value and the baseline tissue impedance
value satisfies a tissue impedance threshold value that is
associated with a change in a congestion status of the patient; and
determining whether a difference between the current pulse transit
time value and the baseline pulse transit time value satisfies a
threshold pulse transit time value that is associated with a change
in a blood pressure status of the patient.
3. The method of claim 1, further comprising, by the processing
circuitry: transmitting the heart failure status of the patient to
a remote computer; receiving, from the remote computer,
instructions for a medical intervention based on the heart failure
status of the patient; and transmitting the instructions for the
medical intervention to a user interface.
4. The method of claim 3, wherein the instructions for the medical
intervention comprise at least one of a change in a drug selection,
a change in a drug dosage, instructions to schedule a visit with a
clinician, and instructions for the patient to seek medical
attention.
5. The method of claim 1, wherein determining the heart failure
status of the patient based on the comparison comprises
determining, by the processing circuitry, a diagnostic score based
on the comparison, wherein the diagnostic score is associated with
a likelihood that the patient will experience an adverse medical
event.
6. The method of claim 5, wherein the heart failure status of the
patient is an updated heart failure status, and wherein determining
the updated heart failure status comprises comparing, by the
processing circuitry, a current diagnostic score to a baseline
diagnostic score of the patient.
7. The method of claim 6, further comprising, by the processing
circuitry, determining the current diagnostic score by at least:
determining a weighted value of the difference between the current
tissue oxygen saturation value and the baseline tissue oxygen
saturation value; determining a weighted value of the difference
between the current tissue impedance value and the baseline tissue
impedance value; determining a weighted value of the difference
between the current pulse transit time value and the baseline pulse
transit time value; and combining the weighted value of the
difference between the current tissue oxygen saturation value and
the baseline tissue oxygen saturation value, the weighted value of
the difference between the current tissue impedance value and the
baseline tissue impedance value, and the weighted value of the
difference between the current pulse transit time value and the
baseline pulse transit time value.
8. The method of claim 1, wherein the signals are current signals,
the method further comprising: receiving a baseline signal from the
at least one optical sensor; receiving a baseline subcutaneous
tissue impedance signal from the first at least two of the
plurality of electrodes; receiving a baseline cardiac electrogram
signal from the second at least two of the plurality of electrodes;
determining at least one of the baseline tissue oxygen saturation
value or the tissue oxygen saturation threshold value based on the
baseline signal received from the at least one optical sensor;
determining at least one of the baseline tissue impedance value or
the tissue impedance threshold value based on the baseline
subcutaneous tissue impedance signal from the first at least two of
the plurality of electrodes; and determining at least one of the
baseline pulse transit time value or the threshold pulse transit
time value based on the baseline cardiac electrogram signal and at
least one of the baseline signal received from the at least one
optical sensor or the baseline subcutaneous tissue impedance
signal.
9. The method of claim 1, wherein the first at least two of the
plurality of electrodes and the second at least two of the
plurality of electrodes include at least one electrode of the
plurality of electrodes in common.
10. The method of claim 1, wherein the implantable medical device
comprises a housing configured for subcutaneous implantation
outside the thorax, and wherein the at least one optical sensor and
the plurality of electrodes are positioned on the housing.
11. The method of claim 1, wherein the implantable medical device
comprises a leadless implantable medical device.
12. A system for determining a heart failure status of a patient
using an implantable medical device configured for subcutaneous
implantation outside of a thorax of the patient, the system
comprising: the implantable medical device comprising: at least one
optical sensor; and a plurality of electrodes; and processing
circuitry configured to: determine a current tissue oxygen
saturation value of the patient based on a signal received from the
at least one optical sensor; determine a current tissue impedance
value of the patient based on a subcutaneous tissue impedance
signal received from a first at least two of the plurality of
electrodes; determine a current pulse transit time value of the
patient based on a cardiac electrogram signal received from a
second at least two of the plurality of electrodes and at least one
of the signal received from the at least one optical sensor and the
subcutaneous tissue impedance signal; compare the current tissue
oxygen saturation value, the current tissue impedance value, and
the current pulse transit time value to corresponding ones of a
baseline tissue oxygenation saturation value, a baseline tissue
impedance value, and a baseline pulse transit time value; and
determine the heart failure status of the patient based on the
comparison.
13. The system of claim 12, wherein the processing circuitry is
configured to compare the current tissue oxygen saturation value,
the current tissue impedance value, and the current pulse transit
time value to the corresponding ones of the baseline tissue
oxygenation saturation value, the baseline tissue impedance value,
and the baseline pulse transit time value by at least: determining
whether a difference between the current tissue oxygen saturation
value and the baseline tissue oxygen saturation value satisfies a
tissue oxygen saturation threshold value that is associated with a
change in a tissue perfusion status of the patient; determining
whether a difference between the current tissue impedance value and
the baseline tissue impedance value satisfies a tissue impedance
threshold value that is associated with a change in a congestion
status of the patient; and determining whether a difference between
the current pulse transit time value and the baseline pulse transit
time value satisfies a threshold pulse transit time value that is
associated with a change in a blood pressure status of the
patient.
14. The system of claim 12, wherein the processing circuitry is
further configured to: transmit the heart failure status of the
patient to a remote computer; receive, from the remote computer,
instructions for a medical intervention based on the heart failure
status of the patient; and transmit the instructions for the
medical intervention to a user interface.
15. The system of claim 14, wherein the instructions for the
medical intervention comprise at least one of a change in a drug
selection, a change in a drug dosage, instructions to schedule a
visit with a clinician, and instructions for the patient to seek
medical attention.
16. The system of claim 12, wherein the processing circuitry is
configured to determine the heart failure status of the patient
based on the comparison by at least determining a diagnostic score
based on the comparison, wherein the diagnostic score is associated
with a likelihood that the patient will experience an adverse
medical event.
17. The system of claim 16, wherein the heart failure status of the
patient is an updated heart failure status, and wherein the
processing circuitry is configured to determine the updated heart
failure status by at least comparing a current diagnostic score to
a baseline diagnostic score of the patient.
18. The system of claim 17, wherein the processing circuitry is
further configured to determine the current diagnostic score by at
least: determining a weighted value of the difference between the
current tissue oxygen saturation value and the baseline tissue
oxygen saturation value; determining a weighted value of the
difference between the current tissue impedance value and the
baseline tissue impedance value; determining a weighted value of
the difference between the current pulse transit time value and the
baseline pulse transit time value; and combining the weighted value
of the difference between the current tissue oxygen saturation
value and the baseline tissue oxygen saturation value, the weighted
value of the difference between the current tissue impedance value
and the baseline tissue impedance value, and the weighted value of
the difference between the current pulse transit time value and the
baseline pulse transit time value.
19. The system of claim 12, wherein the signals are current
signals, and wherein the processing circuitry is further configured
to: receive a baseline signal from the at least one optical sensor,
receive a baseline subcutaneous tissue impedance signal from the
first at least two of the plurality of electrodes, receive a
baseline cardiac electrogram signal from the second at least two of
the plurality of electrodes, determine at least one of the baseline
tissue oxygen saturation value or the tissue oxygen saturation
threshold value based on the baseline signal received from the at
least one optical sensor, determine at least one of the baseline
tissue impedance value or the tissue impedance threshold value
based on the baseline subcutaneous tissue impedance signal from the
first at least two of the plurality of electrodes, and determine at
least one of the baseline pulse transit time value or the threshold
pulse transit time value based on the baseline cardiac electrogram
signal and at least one of the baseline signal received from the at
least one optical sensor or the baseline subcutaneous tissue
impedance signal.
20. The system of claim 12, wherein the first at least two of the
plurality of electrodes and the second at least two of the
plurality of electrodes include at least one electrode of the
plurality of electrodes in common.
21. The system of claim 12, wherein the implantable medical device
comprises a housing configured for subcutaneous implantation
outside the thorax, and wherein the at least one optical sensor and
the plurality of electrodes are positioned on the housing.
22. The system of claim 12, wherein the implantable medical device
comprises a leadless implantable medical device.
23. A system for determining a heart failure status of a patient
using an implantable medical device configured for subcutaneous
implantation outside of a thorax of the patient, the system
comprising: the implantable medical device, comprising: at least
one optical sensor; a plurality of electrodes; and processing
circuitry configured to: determine a current tissue oxygen
saturation value of the patient based on the signal received from
the at least one optical sensor; determine a current tissue
impedance value of the patient based on a subcutaneous tissue
impedance signal received from a first at least two of the
plurality of electrodes; determine a current pulse transit time
value of the patient based on a cardiac electrogram signal received
from a second at least two of the plurality of electrodes and at
least one of the signal received from the at least one optical
sensor and the subcutaneous tissue impedance signal; determine
whether a difference between the current tissue oxygen saturation
value and the baseline tissue oxygen saturation value satisfies a
tissue oxygen saturation threshold value that is associated with a
change in a tissue-perfusion status of the patient; determine
whether a difference between the current tissue impedance value and
the baseline tissue impedance value satisfies a tissue impedance
threshold value that is associated with a change in a congestion
status of the patient; determine whether a difference between the
current pulse transit time value and the baseline pulse transit
time value satisfies a threshold pulse transit time value that is
associated with a change in a blood-pressure status of the patient;
determine the heart failure status of the patient based on at least
one of the difference between the current tissue oxygen saturation
value and the baseline tissue oxygen saturation value, the
difference between the current tissue impedance value and the
baseline tissue impedance value, and the difference between the
current pulse transit time and the baseline pulse transit time; and
transmit the heart failure status of the patient to a remote
computer; and the remote computer, wherein the remote computer
comprises processing circuitry configured to: receive the heart
failure status of the patient transmitted by the processing
circuitry of the implantable medical device; and transmit the
instructions for the medical intervention to a user interface.
24. A system for determining a heart failure status of a patient,
the system comprising: means for determining a current tissue
oxygen saturation value of the patient based on a signal received
from at least one optical sensor; means for determining a current
tissue impedance value of the patient based on a subcutaneous
tissue impedance signal received from a first at least two of a
plurality of electrodes; means for determining a current pulse
transit time value of the patient based on a cardiac electrogram
signal received from a second at least two of the plurality of
electrodes and at least one of the signal received from the at
least one optical sensor and the subcutaneous tissue impedance
signal; means for comparing the current tissue oxygen saturation
value, the current tissue impedance value, and the current pulse
transit time value to corresponding ones of a baseline tissue
oxygenation saturation value, a baseline tissue impedance value,
and a baseline pulse transit time value; and means for determining
the heart failure status of the patient based on the
comparison.
25. The system of claim 24, wherein the means for comparing the
current tissue oxygen saturation value, the current tissue
impedance value, and the current pulse transit time value to the
corresponding ones of the baseline tissue oxygenation saturation
value, the baseline tissue impedance value, and the baseline pulse
transit time value comprises: means for determining whether a
difference between the current tissue oxygen saturation value and
the baseline tissue oxygen saturation value satisfies a tissue
oxygen saturation threshold value that is associated with a change
in a tissue perfusion status of the patient; means for determining
whether a difference between the current tissue impedance value and
the baseline tissue impedance value satisfies a tissue impedance
threshold value that is associated with a change in a congestion
status of the patient; and means for determining whether a
difference between the current pulse transit time value and the
baseline pulse transit time value satisfies a threshold pulse
transit time value that is associated with a change in a blood
pressure status of the patient.
26. A non-transitory computer-readable medium storing instructions
for causing processing circuitry to perform a method for
determining a heart failure status of a patient using an
implantable medical device configured for subcutaneous implantation
outside of a thorax of the patient, the implantable medical device
comprising a plurality of electrodes and at least one optical
sensor, the method comprising: determining a current tissue oxygen
saturation value of the patient based on a signal received from the
at least one optical sensor; determining a current tissue impedance
value of the patient based on a subcutaneous tissue impedance
signal received from a first at least two of the plurality of
electrodes; determining a current pulse transit time value of the
patient based on a cardiac electrogram signal received from a
second at least two of the plurality of electrodes and at least one
of the signal received from the at least one optical sensor and the
subcutaneous tissue impedance signal; comparing the current tissue
oxygen saturation value, the current tissue impedance value, and
the current pulse transit time value to corresponding ones of a
baseline tissue oxygenation saturation value, a baseline tissue
impedance value, and a baseline pulse transit time value; and
determining the heart failure status of the patient based on the
comparison.
27. The non-transitory computer-readable medium of claim 26,
wherein the method further comprises: determining whether a
difference between the current tissue oxygen saturation value and
the baseline tissue oxygen saturation value satisfies a tissue
oxygen saturation threshold value that is associated with a change
in a tissue perfusion status of the patient; determining whether a
difference between the current tissue impedance value and the
baseline tissue impedance value satisfies a tissue impedance
threshold value that is associated with a change in a congestion
status of the patient; and determining whether a difference between
the current pulse transit time value and the baseline pulse transit
time value satisfies a threshold pulse transit time value that is
associated with a change in a blood pressure status of the
patient.
28. A system for determining a heart failure status of a patient,
the system comprising: one or more sensors configured to monitor
one or more parameters of the patient; and processing circuitry
configured to: determine current values of the one or more
parameters of the patient based on one or more signals received
from the one or more sensors, the one or more parameters comprising
a surrogate parameter for congestion, a surrogate parameter for
tissue perfusion, and a surrogate parameter for blood pressure;
compare the current value of the surrogate parameter for
congestion, the current value of the surrogate parameter for tissue
perfusion, and the current value of the surrogate parameter for
blood pressure to corresponding ones of a baseline value of the
surrogate parameter for congestion, a baseline value of the
surrogate parameter for tissue perfusion, and a baseline value of
the surrogate parameter for blood pressure; and determine the heart
failure status of the patient based on the comparison.
Description
TECHNICAL FIELD
[0001] The disclosure relates generally to medical device systems
and, more particularly, medical device systems configured to
monitor patient parameters.
BACKGROUND
[0002] Some types of implantable medical devices (IMDs) may be used
to monitor one or more physiological parameters of a patient, such
as physiological parameters associated with cardiac function. Such
IMDs may include, or may be part of a system that includes, sensors
that detect signals associated with such physiological parameters;
e.g., cardiac depolarization or tissue impedance. Values determined
based on such signals may be used to assist in detecting changes in
cardiac conditions such as heart failure, in evaluating the
efficacy of a therapy, or in generally evaluating cardiac
health.
[0003] Implantable devices that monitor physiological parameters
related to a heart failure condition of a patient may evaluate
values associated with the physiological parameters, such as to
determine whether the values satisfy a threshold or have changed.
Values that satisfy a threshold or that have changed may indicate
that a therapy being administered to the patient is not effectively
managing the patient's heart failure condition.
SUMMARY
[0004] In general, this disclosure is directed to techniques for
determining a heart failure status of a patient. Such techniques
may include performing assessments associated with aspects of a
patient's cardiac function, and determining a hemodynamic profile
of the patient based on the outcome of the assessments. Such
hemodynamic profiles may indicate a heart failure status of the
patient, e.g., whether the patient's heart failure status is stable
or progressing, and may help guide therapy selection.
[0005] When a patient presents at a healthcare facility with acute
heart failure symptoms, a clinician may perform assessments
associated with aspects of the patient's cardiac function, such as
preload, afterload, and perfusion, by observing surrogate
parameters. For example, in order to assess preload (a measure of
heart filling capacity), a clinician may observe the patient for
signs of congestion, such as peripheral edema, jugular venous
dilatation, ascites, or others. To assess afterload (a measure of
vascular resistance) a clinician may use blood pressure
measurements as a surrogate parameter to determine whether the
patient's vascular resistance is high and therefore indicative of
vasoconstriction. To assess perfusion (an indication of supply or
cardiac output versus metabolic demand or body surface area) a
clinician may observe the patient for signs of inadequate
peripheral perfusion, such as cold sweated extremities, oliguria,
mental confusion, dizziness, and numbness and tingling in
extremities. Based on the combined outcome of these assessments, a
clinician may identify a hemodynamic profile of the patient (e.g.,
congested+vasoconstricted+adequately perfused), and prescribe
treatment in accordance with the hemodynamic profile. Such
treatment may include drug therapy to compensate for a loss of
cardiac function caused by the patient's heart failure condition.
Thereafter, the patient may be discharged from the healthcare
facility with instructions for continuing the prescribed therapy
and scheduling regular clinician visits.
[0006] For one or more reasons, however, a patient's heart failure
condition, which may be in a state of chronic but stable
decompensation when adequately managed by therapy, may become
unstable and acutely decompensate, that is, no longer adequately be
managed by therapy, between clinician visits. For example, the
progressive nature of heart disease may cause a patient not
exhibiting congestion at a previous clinician visit to become
congested between visits, which may be due to physiological cardiac
remodeling that occurs in the progression of HF. Or, a confounding
factor such as over-the-counter medication intake may be eliminated
or introduced, leading to a change in vasoconstriction. In any such
cases, the patient may become symptomatic and acutely decompensate
between visits. In some examples, such acute decompensation may
lead to hospitalization or other adverse medical events.
Consequently, clinical outcomes for heart-failure patients would
benefit from methods for updating a patient's hemodynamic profile
and heart failure status between clinician visits, which in turn
may enable prediction of a likelihood that an acute decompensation
and hospitalization may occur. In response to such a prediction, a
patient's treatment may be adjusted (e.g., by modifying a drug
regimen), which may help reduce the patient's likelihood of acute
decompensation and hospitalization.
[0007] However, assessment of a patient's heart failure status
based on observations of the surrogate parameters of congestion
(i.e., hypervolemia), peripheral perfusion, and vascular resistance
may be limited to clinical or hospital settings. For example, such
assessments may require medical expertise unavailable to the
patient in a non-clinical environment. Thus, methods for updating a
patient's hemodynamic profile between clinician visits may be
performed using one or more medical devices, such as the
subcutaneously-implantable medical devices described herein.
[0008] Accordingly, techniques described herein may include
automatically detecting and monitoring parameters associated with
cardiac function that are measurable by one or more medical
devices, which may include a subcutaneously implantable medical
device, which may in some cases be leadless. As with a clinician's
assessments, such parameters may be indicative of congestion,
peripheral perfusion, and vascular resistance or blood pressure.
When taken together, this three-part evaluation of a patient's
cardiac function may provide a robust indication of whether a heart
failure status of the patient has changed, which may be useful in
detecting, or assessing the patient's likelihood of, acute
decompensation and in proactively modifying the patient's therapy.
Because the methods described herein are intended to be performed
by one or more medical devices in between clinician visits, such
methods may use sensors, such as electrodes and optical sensors, to
monitor certain parameters of the patient's cardiac function in
place of the signs observed by a clinician.
[0009] For example, instead of assessing external signs of
congestion, some of the methods described herein include
determining a subcutaneous tissue impedance value (Z), which is a
surrogate for congestion. Instead of assessing signs of peripheral
perfusion, some of the methods described herein include determining
a tissue oxygen saturation (StO.sub.2) value, which provides a
surrogate for cardiac output and peripheral perfusion. Instead of
assessing vascular resistance via blood pressure measurements, some
of the methods described herein include determining a pulse transit
time (PTT) value. It should be noted that, although not strictly
equivalent, vascular resistance and blood pressure may be described
interchangeably as being assessable by PTT. In some examples, PTT
may be used to determine a measurement of pulse wave velocity
(PWV), the former of which indicates the time it takes a pulse wave
(e.g., of an ECG signal) to travel over an estimable distance
within the patient. In such examples, the estimable distance
traveled by the pulse wave may be divided by a determined PTT value
to arrive at a PWV value. The PWV value may be used instead of or
in addition to the PTT value in assessing vascular resistance but,
for a given patient, the estimable distance can be assumed
constant, and changes in PTT considered representative of changes
in PWV. For the sake of clarity, the techniques described herein
are described as assessing vascular resistance based on PTT.
[0010] A comparison of current values of Z, StO.sub.2, or PTT to
corresponding baseline values may be used to determine a status of
the patient's heart failure condition, such as whether the
condition is stable or has changed, e.g., progressed or worsened.
In techniques described herein, a one or more IMDs may determine a
patient's heart failure status and transmit the heart failure
status to a remote computer or other device external to the
patient. In some cases, the patient's heart failure status may
indicate whether the patient is congested, inadequately perfused,
or vasoconstricted, and may further indicate the patient's
likelihood of decompensation or hospitalization. The remote
computer then may transmit instructions for a medical intervention
(e.g., instructions for changes to a drug regimen), to a user
device used by the patient or a caregiver. In this manner, a
patient's heart failure treatment may be modified as needed in
between clinic visits, which may help avoid adverse medical events
such as recurrent symptoms or hospitalization.
[0011] In examples in which a clinician is involved in determining
the instructions for the medical intervention, the techniques
described herein may enable the clinician to make determinations
regarding the medical intervention by accounting for the
interrelated nature of the physiological causes of the patient's Z,
StO.sub.2, or PTT values. For example, a downward trend in a Z
value may indicate that the patient's likelihood of congestion has
increased, but the clinician may be hesitant to modify the
patient's drug regimen on this basis alone. However, by
additionally providing StO.sub.2 and PTT values, the techniques
described herein may enable the clinician to determine whether a
particular modification to the patient's drug regimen to address
potential congestion (e.g., increasing a dosage of a diuretic drug)
may be desirable. In this manner, the techniques described herein
may increase the clinician's confidence in prescribing a particular
medical intervention, which may lead to improved clinical outcomes
for the patient.
[0012] In one example, a method for determining a heart failure
status of a patient using an implantable medical device configured
for subcutaneous implantation outside of a thorax of the patient,
the implantable medical device comprising a plurality of electrodes
and at least one optical sensor, comprises, by processing circuitry
of a medical device system comprising the implantable medical
device: determining a current tissue oxygen saturation value of the
patient based on a signal received from the at least one optical
sensor; determining a current tissue impedance value of the patient
based on a subcutaneous tissue impedance signal received from a
first at least two of the plurality of electrodes; determining a
current pulse transit time value of the patient based on a cardiac
electrogram signal received from a second at least two of the
plurality of electrodes and at least one of the signal received
from the at least one optical sensor and the subcutaneous tissue
impedance signal; comparing the current tissue oxygen saturation
value, the current tissue impedance value, and the current pulse
transit time value to corresponding ones of a baseline tissue
oxygenation saturation value, a baseline tissue impedance, and a
baseline pulse transit time value; and determining the heart
failure status of the patient based on the comparison.
[0013] In another example, a system for determining a heart failure
status of a patient using an implantable medical device configured
for subcutaneous implantation outside of a thorax of the patient
comprises the implantable medical device, which comprises at least
one optical sensor; and a plurality of electrodes; and processing
circuitry configured to: determine a current tissue oxygen
saturation value of the patient based on a signal received from the
at least one optical sensor; determine a current tissue impedance
value of the patient based on a subcutaneous tissue impedance
signal received from a first at least two of the plurality of
electrodes; determine a current pulse transit time value of the
patient based on a cardiac electrogram signal received from a
second at least two of the plurality of electrodes and at least one
of the signal received from the at least one optical sensor and the
subcutaneous tissue impedance signal; compare the current tissue
oxygen saturation value, the current tissue impedance value, and
the current pulse transit time value to corresponding ones of a
baseline tissue oxygenation saturation value, a baseline tissue
impedance, and a baseline pulse transit time value; and determine
the heart failure status of the patient based on the
comparison.
[0014] In another example, a system for determining a heart failure
status of a patient using an implantable medical device configured
for subcutaneous implantation outside of a thorax of the patient
comprises the implantable medical device, which comprises: at least
one optical sensor; a plurality of electrodes; and processing
circuitry configured to: determine a current tissue oxygen
saturation value of the patient based on the signal received from
the at least one optical sensor; determine a current tissue
impedance value of the patient based on a subcutaneous tissue
impedance signal received from a first at least two of the
plurality of electrodes; determine a current pulse transit time
value of the patient based on a cardiac electrogram signal received
from a second at least two of the plurality of electrodes and at
least one of the signal received from the at least one optical
sensor and the subcutaneous tissue impedance signal; determine
whether a difference between the current tissue oxygen saturation
value and the baseline tissue oxygen saturation value satisfies a
tissue oxygen saturation threshold value that is associated with a
change in a tissue-perfusion status of the patient; determine
whether a difference between the current tissue impedance value and
the baseline tissue impedance value satisfies a tissue impedance
threshold value that is associated with a change in a congestion
status of the patient; determine whether a difference between the
current pulse transit time value and the baseline pulse transit
time value satisfies a threshold pulse transit time value that is
associated with a change in a blood-pressure status of the patient;
determine the heart failure status of the patient based on at least
one of the difference between the current tissue oxygen saturation
value and the baseline tissue oxygen saturation value, the
difference between the current tissue impedance value and the
baseline tissue impedance value, and the difference between the
current pulse transit time and the baseline pulse transit time; and
transmit the heart failure status of the patient to a remote
computer; and the remote computer, wherein the remote computer
comprises processing circuitry configured to: receive the heart
failure status of the patient transmitted by the processing
circuitry of the implantable medical device; and transmit the
instructions for the medical intervention to a user device.
[0015] In another example, a system for determining a heart failure
status of a patient comprises means for determining a current
tissue oxygen saturation value of the patient based on a signal
received from at least one optical sensor; means for determining a
current tissue impedance value of the patient based on a
subcutaneous tissue impedance signal received from a first at least
two of a plurality of electrodes; means for determining a current
pulse transit time value of the patient based on a cardiac
electrogram signal received from a second at least two of the
plurality of electrodes and at least one of the signal received
from the at least one optical sensor and the subcutaneous tissue
impedance signal; means for comparing the current tissue oxygen
saturation value, the current tissue impedance value, and the
current pulse transit time value to corresponding ones of a
baseline tissue oxygenation saturation value, a baseline tissue
impedance, and a baseline pulse transit time value; and means for
determining the heart failure status of the patient based on the
comparison.
[0016] In another example, a non-transitory computer-readable
medium stores instructions for causing processing circuitry to
perform a method for determining a heart failure status of a
patient using an implantable medical device configured for
subcutaneous implantation outside of a thorax of the patient, the
implantable medical device comprising a plurality of electrodes and
at least one optical sensor, the method comprising determining a
current tissue oxygen saturation value of the patient based on a
signal received from the at least one optical sensor; determining a
current tissue impedance value of the patient based on a
subcutaneous tissue impedance signal received from a first at least
two of the plurality of electrodes; determining a current pulse
transit time value of the patient based on a cardiac electrogram
signal received from a second at least two of the plurality of
electrodes and at least one of the signal received from the at
least one optical sensor and the subcutaneous tissue impedance
signal; comparing the current tissue oxygen saturation value, the
current tissue impedance value, and the current pulse transit time
value to corresponding ones of a baseline tissue oxygenation
saturation value, a baseline tissue impedance, and a baseline pulse
transit time value; and determining the heart failure status of the
patient based on the comparison.
[0017] In another example, a system for determining a heart failure
status of a patient comprises one or more sensors configured to
monitor one or more parameters of the patient; and processing
circuitry configured to: determine current values of the one or
more parameters of the patient based on one or more signals
received from the one or more sensors, the one or more parameters
comprising a surrogate parameter for congestion, a surrogate
parameter for tissue perfusion, and a surrogate parameter for blood
pressure; compare the current value of the surrogate parameter for
congestion, the current value of the surrogate parameter for tissue
perfusion, and the current value of the surrogate parameter for
blood pressure to corresponding ones of a baseline value of the
surrogate parameter for congestion, a baseline value of the
surrogate parameter for tissue perfusion, and a baseline value of
the surrogate parameter for blood pressure; and determine the heart
failure status of the patient based on the comparison.
[0018] This summary is intended to provide an overview of the
subject matter described in this disclosure. It is not intended to
provide an exclusive or exhaustive explanation of the apparatus and
methods described in detail within the accompanying drawings and
description below. The details of one or more aspects of the
disclosure are set forth in the accompanying drawings and the
description below.
BRIEF DESCRIPTION OF DRAWINGS
[0019] The details of one or more examples of this disclosure are
set forth in the accompanying drawings and the description below.
Other features, objects, and advantages of this disclosure will be
apparent from the description and drawings, and from the
claims.
[0020] FIG. 1 is a conceptual drawing illustrating an example of a
medical device system including a leadless implantable medical
device and an external device in conjunction with a patient;
[0021] FIG. 2 is a conceptual drawing illustrating an example
configuration of the leadless implantable medical device of the
medical device system of FIG. 1;
[0022] FIG. 3 is a functional block diagram illustrating another
perspective of the example configuration of the leadless
implantable medical device of FIG. 1;
[0023] FIGS. 4A and 4B are block diagrams illustrating other
example leadless implantable medical devices substantially similar
to the implantable medical device of FIG. 1;
[0024] FIG. 5 is a block diagram illustrating an example system
that includes an external device, such as a server, and one or more
computing devices that are coupled to the leadless implantable
medical device of FIG. 1 and the external device of FIG. 1 via a
network;
[0025] FIG. 6 is a flow diagram illustrating an example technique
for determining a heart failure status of a patient based on a
comparison of current tissue oxygen saturation, impedance, and
pulse transit time values to corresponding baseline values, and
transmitting the heart failure status to a remote computer;
[0026] FIG. 7 is a flow diagram illustrating an example technique
for determining the baseline or current values of tissue impedance,
tissue oxygen saturation, and pulse transit time of FIG. 6;
[0027] FIG. 8 is a flow diagram illustrating an example technique
for determining a current diagnostic score and determining an
updated heart failure status of a patient based on a comparison of
the current diagnostic score to a baseline diagnostic score;
[0028] FIG. 9 is a flow diagram illustrating an example technique
for a remote computer to determine instructions for a medical
intervention based on a heart failure status received from the
leadless implantable medical device of FIG. 1, and transmit the
instructions to a user interface;
[0029] FIG. 10 is a flow diagram illustrating an example technique
for determining appropriate medical interventions for a
hypervolemic patient based on trends in the patient's tissue oxygen
saturation and pulse transit time;
[0030] FIG. 11 is a flow diagram illustrating an example technique
for determining appropriate medical interventions for a hypovolemic
patient based on trends in the patient's tissue oxygen saturation
and pulse transit time; and
[0031] FIG. 12 is a flow diagram illustrating an example technique
for determining appropriate medical interventions for an
optivolemic patient based on trends in the patient's tissue oxygen
saturation and pulse transit time.
DETAILED DESCRIPTION
[0032] In general, this disclosure describes example techniques
related to determining a heart failure status of a patient based on
physiological parameters associated with cardiac function monitored
by one or more medical devices. A subcutaneous IMD may be used in
some examples of the techniques, and may be configured for
placement under the skin of a patient's torso, such as between the
skin and a pectoral muscle. In some examples, processing circuitry
may determine current Z, StO.sub.2, and PTT values of the patient
based on signals detected by a plurality of electrodes and one or
more optical sensors, e.g., of the subcutaneous IMD. In some
examples, the IMD may be leadless, and the optical sensors and
electrodes may be integrated with and/or connected to a housing of
the IMD.
[0033] The processing circuitry may compare the current Z,
StO.sub.2, and PTT values to corresponding baseline values, which
may be stored in a memory of the IMD. Based on differences between
the current values and the baseline values, the processing
circuitry may determine a current hemodynamic profile of a heart
failure status of the patient. For example, the processing
circuitry may determine that a change in the patient's cardiac
function and/or compensation status has occurred, and transmit the
heart failure status to a remote computer. It is further
contemplated that, in some examples, the remote computer may
transmit instructions for medical intervention to a user device
based on the heart failure status.
[0034] Techniques that monitor one or more aspects of cardiac
function, such as by measuring transthoracic impedance and/or PTT,
do not provide a robust assessment of a patient's heart failure
status that may be obtained by a combined assessment of Z,
StO.sub.2, and PTT. Indeed, two patients with hemodynamic profile
that vary by one of these three parameters may have different heart
failure statuses, and thus different treatment requirements. For
example, the two patients each may have impedance and PTT values
that reflect congestion and non-vasoconstriction. However, an
StO.sub.2 value of the first patient may reflect adequate
peripheral perfusion, whereas an StO.sub.2 value of the second
patient may reflect inadequate peripheral perfusion. The
hemodynamic profile of the first patient thus may be characterized
as "warm and wet" (i.e., adequately perfused and congested),
whereas the profile of the second patient is "cold and wet" (i.e.,
inadequately perfused and congested). Prognosis and the treatment
requirements of these two patients differ based on their differing
peripheral perfusion statuses. For example, the "cold and wet"
patient may be at higher risk of acute decompensation and require a
downward titration of a beta-blocker drug to help increase heart
rate, whereas a different treatment modification may be required
for the "warm and wet" patient. Thus, monitoring of only tissue
impedance and/or PTT may be inadequate to fully assess a patient's
heart failure status for the purpose of predicting adverse medical
events (e.g., acute decompensation or hospitalization) and
identifying appropriate treatment options.
[0035] Various techniques for monitoring cardiac function may be
more or less invasive and/or prone to inaccuracy. For example,
sensing transthoracic impedance values or producing an ECG with
signals obtained from electrodes on leads placed within the
thoracic cavity, such as within the heart, may be more invasive
than sensing parameters, e.g., Z, StO.sub.2, and PTT, via a
subcutaneous 1 MB. Some methods may use electrodes or optical
sensors positioned at peripheral sites on the patient to monitor
parameters such as PTT. However, values determined based on signals
from peripherally-located sensors may be more prone to motion
artifacts generated by patient movement than values determined by
sensors placed centrally, e.g., subcutaneously outside the thorax.
In addition, peripheral sensor based PTT measurement techniques may
require multiple measuring devices to be synchronized together,
which may provide additional opportunities for measurement
inaccuracy. Moreover, while other methods for monitoring cardiac
function may include generating an alert if a measurement satisfies
a threshold, a limitation of such methods is that they do not
include providing instructions to the patient for a medical
intervention based on such alerts.
[0036] In some example techniques described herein, a patient's
hemodynamic profile and heart failure status may be determined
using a subcutaneous implantable device configured to measure all
three of Z, StO.sub.2, and PTT from a single location, which may be
near a patient's pectoral muscle. Such measurements may be repeated
at predetermined intervals, such as hourly or daily. The device
then may determine a heart failure status of the patient based on
current and baseline values of Z, StO.sub.2, and PTT, and transmit
the heart failure status via wireless communication to a remote
computer, which then may transmit instructions for medical
intervention to a user device (e.g., a smartphone or tablet,
located with the patient or a caregiver). Thus, in some cases, the
techniques described herein advantageously may provide robust and
accurate assessment of a patient's heart failure status at regular
intervals and enable modification of a patient's treatment between
clinician visits, which in turn may provide improved clinical
outcomes.
[0037] FIG. 1 illustrates the environment of an example medical
device system 2 in conjunction with a patient 4 and a heart 6, in
accordance with an apparatus and method of certain examples
described herein. The example techniques may be used with a
leadless subcutaneously-implantable medical device (IMD) 10, which
may be in wireless communication with external device 12. In some
examples, IMD 10 may be implanted outside of a thoracic cavity of
patient 4 (e.g., subcutaneously in the pectoral location
illustrated in FIG. 1). IMD 10 may be positioned near the sternum
near or just below the level of heart 6, e.g., at least partially
within the cardiac silhouette. In some examples, IMD 10 may take
the form of a Reveal LINQ.TM. Insertable Cardiac Monitor (ICM),
available from Medtronic plc, of Dublin, Ireland. External device
12 may be a computing device configured for use in settings such as
a home, clinic, or hospital, and may further be configured to
communicate with IMD 10 via wireless telemetry. For example,
external device 12 may be coupled to a remote patient monitoring
system, such as Carelink.RTM., available from Medtronic plc, of
Dublin, Ireland. External device 12 may, in some examples, comprise
a programmer, an external monitor, or a consumer device such as a
smart phone or tablet.
[0038] IMD 10 may include a plurality of electrodes and one or more
optical sensors, which collectively detect signals that enable
processing circuitry, e.g., of the IMD 10, to determine current
values of subcutaneous Z, StO.sub.2, and PTT for patient 4, and
determine a heart failure status of patient 4 based on such values.
For example, the plurality of electrodes may be configured to
detect a signal indicative of a Z value of the extracellular or
extra-vascular fluid in the tissue surrounding and the IMD 10.
Thus, in some examples, a Z value may indicate the presence of
peripheral edema as a consequence of congestion. Processing
circuitry of IMD 10 may use the Z value of the tissue surrounding
the IMD to determine a congestion status of patient 4. In some
examples, processing circuitry of IMD 10 also may use the Z value
in conjunction with an ECG signal detected by the plurality of
electrodes to determine a PTT value of patient 4. In other
examples, processing circuitry of IMD 10 may use signals detected
by one or more optical sensors positioned on a surface of IMD 10 to
determine a PTT value in conjunction with the ECG signal.
Processing circuitry of IMD 10 also may use signals detected by the
one or more optical sensors to determine an StO.sub.2 value of
patient 4.
[0039] After determining current values for Z, StO.sub.2, and PTT
of patient 4, processing circuitry, e.g., of IMD 10, may compare
such current values to corresponding baseline values, e.g., stored
in a memory of IMD 10, to determine differences therebetween. If
the differences between one or more of the current and
corresponding baseline values satisfies a threshold, then the
processing circuitry may determine that a heart failure status of
patient 4 has changed relative to a time when the baseline values
were established. Regardless of whether any such differences
satisfy a threshold, IMD 10 then may wirelessly transmit the heart
failure status of patient 4 to external device 12. The heart
failure status may include a diagnostic score of patient 4, which
may be associated with a likelihood that patient 4 will acutely
decompensate and require hospitalization within a certain period of
time. IMD 10 may transmit a heart failure status of patient 4 to
external device 12 at predetermined intervals, such as daily,
weekly, or at any other desired period.
[0040] In some examples, an interval at which IMD 10 determines a
heart failure status of patient 4 is the same as an interval at
which IMD 10 transmits the heart failure status to external device
12. In other examples, IMD 10 may determine a heart failure status
of patient 4 more frequently than IMD 10 transmits a heart failure
status to external device 12. By determining a heart failure status
more often than a heart failure status is transmitted, an accuracy
of a technique for determining a heart failure status may be
enhanced by eliminating outlier measurements. For example, IMD 10
may determine that a difference between a current Z, StO.sub.2, or
PTT of patient 4 and a corresponding baseline satisfies a threshold
only if a certain number or proportion of preceding results
satisfied the threshold. In other examples, a single incident in
which a current value satisfied a threshold may suffice to cause
IMD 10 to determine that a change in heart failure status of
patient 4 has occurred. In some examples, a clinician may configure
a sensitivity of IMD 10 to certain types of values that satisfy a
threshold at or after the time of implant of IMD 10, depending on
factors such as the individual condition of patient 4. As discussed
below, several aspects of the operation of IMD 10 may be configured
by a clinician to help achieve improved monitoring and clinical
outcomes for individual patients such as patient 4.
[0041] At or after the time of implantation of IMD 10 into the
subcutaneous location illustrated in FIG. 1, a clinician may
configure one or more aspects of IMD 10. In some examples, a
clinician may establish baseline values of Z, StO.sub.2, and PTT
using conventional assessments. For example, the clinician may use
stethoscope to listen for congestion, conduct arterial and venous
blood draws with co-oximeter measurements to assess perfusion, and
apply a blood pressure cuff to approximate vascular resistance. In
addition, the clinician may complete a standard examination and
assessment of patient 4's congestion, peripheral perfusion, and
vascular resistance statuses. For example, the clinician may
identify whether, and to what extent, congestion is present. The
clinician then may use an application on a tablet or other smart
device to enter empirically-determined baseline values of Z,
StO.sub.2, and PTT into a memory of the IMD 10, along with patient
4's status with respect to congestion, peripheral perfusion, and
vascular resistance.
[0042] In other examples, instead of determining baseline values
for Z, StO.sub.2, and PTT using the conventional assessment noted
above, a clinician may conduct the standard examination and
assessment of patient 4's congestion, peripheral perfusion, and
vascular resistance statuses. Based on the outcome of this
assessment, and optionally on other data corresponding to patient
4, the clinician may select baseline values of Z, StO.sub.2, and
PTT for patient 4. Lists or tables of such values may be presented
by the app on the clinician tablet or other smart device, or may be
available from a centralized database. Once the clinician has
selected appropriate baseline values for patient 4, he or she may
use the app to store the values in IMD 10.
[0043] In still other examples, IMD 10 may be configured to
undertake a learning phase after implantation into patient 4, in
which IMD 10 determines the baseline values of Z, StO.sub.2, and
PTT (where the baseline value PTT is determined based on a baseline
cardiac electrogram signal plus a baseline optical signal or a
baseline Z) for patient 4 based on values collected by IMD 10 over
a period of time, and stores the values in a memory of IMD 10. For
example, IMD 10 may measure Z, StO.sub.2, and PTT on a relatively
frequent basis (e.g., hourly or several times a day) for a period
of time (e.g., a week or more) to determine baseline values during
a period when the condition of patient 4 is stable and not acutely
decompensating.
[0044] Because heart failure is a progressive disease, values for
baselines, thresholds, and event identifiers associated with
patient 4 also may be updated periodically. For example, IMD 10 may
undertake a new learning phase monthly, quarterly, yearly, or at an
expiration of any other appropriate period. The new learning phase
may produce new values associated with one or more of the
baselines, thresholds, and evidence levels based on an updated
heart failure status of patient 4. In other examples, a clinician
may program IMD 10 to update such values as needed, such as
following a health event experienced by patient 4 that may affect
the applicability of such values to patient 4's heart failure
status.
[0045] In some examples, IMD 10 may determine baseline values based
on averages of the Z, StO.sub.2, and PTT values collected during
the training period. In other examples, IMD 10 may reject outlier
values collected during the training period prior to determining
the baseline values, although IMD may use other methods of
determining baseline values from collected values. In some examples
in which IMD 10 uses a training period to determine the baseline
values, a clinician also may conduct the standard examination and
assessment of congestion, peripheral perfusion, and vascular
resistance statuses of patient 4, and store the values in IMD
10.
[0046] In addition to determining baseline values of Z, StO.sub.2,
and PTT for patient 4, IMD 10 or a clinician also may determine
threshold values of Z, StO.sub.2, and PTT for patient 4 and store
the threshold values in a memory of IMD 10. In some examples, a
threshold value may be indicative of a value of a difference
between a current value of one of Z, StO.sub.2, or PTT and a
corresponding baseline value that indicates that a heart failure
status of patient 4 may have changed. For example, a determination
by IMD 10 of a heart failure status of patient 4 may be based, at
least in part, on whether any of the differences between the
current values of Z, StO.sub.2, or PTT and the corresponding
baseline values satisfy a threshold value.
[0047] IMD 10 may determine threshold values for each of a number
of different baseline values for each of Z, StO.sub.2, and PTT,
such as during the training period of IMD 10. In some examples, IMD
10 may automatically associate a particular threshold value with a
particular baseline value of one of Z, StO.sub.2, or PTT for
patient 4. In other examples, IMD 10 may determine a threshold
value for the one of Z, StO.sub.2, or PTT based in part on the
values of the other baselines determined for patient 4. For
example, if a baseline Z value of patient 4 indicates that patient
4 is congested, IMD 10 may select a lower threshold value for
StO.sub.2 than if the baseline Z value does not indicate that
patient 4 is congested. In this way, IMD 10's determinations of
heart failure status may be more sensitive for patients that are at
a higher overall risk for acute decompensation, or for whom acute
decompensation may have greater health consequences. In other
examples, a clinician may choose to program IMD 10 to apply
relatively higher or lower thresholds than those selected by
processing circuitry of IMD 10 based on other considerations known
to the clinician.
[0048] Regardless of whether the threshold values for Z, StO.sub.2,
and PTT are determined by processing circuitry of IMD 10 during a
training period or by a clinician, such threshold values may be
updated at one or more times after implantation of IMD 10. For
example, threshold values may be updated after patient 4
experiences an acute decompensation or hospitalization event, which
may indicate that one or more parameters of a heart failure
condition of patient 4 has progressed or otherwise changed. Or, the
threshold values may be updated at the expiration of a time period
(e.g., weekly, monthly, or yearly following implantation of IMD
10). Such updates to the threshold values may be performed
automatically by processing circuitry of IMD 10, or manually by a
clinician. In any such examples, the updated threshold values may
be determined based on trends in one or more of the current values
of Z, StO.sub.2, and PTT during the preceding time period. In this
manner, the threshold values used in the techniques described
herein may be modified as needed to account for changes in patient
4's hemodynamic profile.
[0049] In addition to determining whether the differences between
any current values of Z, StO.sub.2, or PTT and corresponding
baseline values satisfy one or more threshold values, IMD 10 also
may determine a diagnostic score for patient 4 based on the current
values of Z, StO.sub.2, and PTT. A diagnostic score may be a value
(e.g., a numeric value) that is associated with a likelihood that
patient 4 will acutely decompensate and/or require hospitalization
within a certain period of time, regardless of whether the
differences between any current values of Z, StO.sub.2, or PTT and
corresponding baseline values satisfy one or more threshold values.
In some examples, a diagnostic score of patient 4 may be further
increased if one or more such differences satisfy a threshold
value.
[0050] IMD 10 may determine a diagnostic score of patient 4 based,
at least in part, on values of evidence levels that may be
associated with values of various parameters of heart failure. In
some examples, such evidence levels may be determined based on
assessments of one or more populations of patients with heart
failure conditions. Diagnostic scores may comprise one or more
values associated with one or more evidence levels, with each
evidence level being associated with a value of a parameter of
heart failure. For example, assessments of patient populations may
classify parameters (e.g., congestion, inadequate perfusion,
vasoconstriction/vasodilation) as occurring at varying levels of
severity. Each level of severity of each parameter may be
characterized as an "evidence level" associated with a numerical
value, and patient outcomes (e.g., prior patient population data)
for each evidence level may be documented. In light of patient
outcomes, the numerical values associated with the evidence levels
may be weighted to reflect their predictive value of patient
outcome.
[0051] IMD 10 may determine a diagnostic score associated with a
heart failure status of patient 4 based on a combination of the
evidence levels associated with the current values of Z, StO.sub.2,
and PTT of patient 4. For example, the diagnostic score may be
based on an integration of prior population data (e.g., data
associated with the evidence levels) with measurements specific to
patient 4 (e.g., the current values of Z, StO.sub.2, or PTT of
patient 4), such as by using Bayesian statistics or other methods
of machine learning. In some examples, an algorithm trained using
clinician-scored, prior population data is applied to
patient-specific measurements of parameters, such as the current
values of Z, StO.sub.2, or PTT, to determine a diagnostic score. In
some examples, a diagnostic score determined based on a combination
of evidence levels may indicate a likelihood that patient 4
underwent a change in each of the corresponding parameters of heart
failure associated with the evidence levels. For example, an
evidence level associated with a current value of Z may indicate an
X % chance that patient 4 underwent a change in congestion status
during a preceding time period on which the diagnostic score is
based. Similarly, an evidence level associated with a current value
of StO.sub.2 or PTT may indicate a Y % or Z % chance that patient 4
underwent a change in respective ones of a tissue perfusion or
blood pressure status during the preceding time period. In some
examples, the diagnostic score may be adjusted upward or downward
based on how many of the differences between the current values of
patient 4 and the corresponding baseline values satisfy associated
thresholds. In addition, a clinician may manually modify weights
assigned by IMD 10 to evidence levels for different measured
parameters, depending on an individual condition or medical history
of patient 4. For example, the clinician may manually modify one or
more of the weights assigned by IMD 10 based on events in the
medical history of patient 4 such as hospital admissions for heart
failure, medication changes, history of systolic heart failure,
hypertension, respiratory illness (e.g., COPD), diabetes, atrial
fibrillation, renal failure, one or more blood disorders (e.g.,
anemia), one or more sleep disorders (e.g., sleep apnea), among
others. In any such examples, the evidence levels associated with
the parameters of Z, StO.sub.2, and PTT may be stored in a memory
of IMD 10.
[0052] In some examples, a diagnostic score, as described above,
may be a baseline diagnostic score associated with a heart failure
status of patient 4. Because heart failure is a progressive
disease, IMD 10 periodically may determine an updated heart failure
status of patient 4 at regular intervals. In some examples, IMD 10
may determine an updated heart failure status of patient 4 by
iteratively performing the methods described above. In other
examples, an updated heart failure status of patient 4 determined
by IMD 10 may be based, at least in part, on a determination of a
current diagnostic score of patient 4 and a comparison of the
current diagnostic score to a previously-determined diagnostic
score of patient 4 (e.g., a baseline diagnostic score).
[0053] In such examples, IMD 10 may determine a current diagnostic
score of patient 4 by combining weighted values associated with the
current values of Z, StO.sub.2, and PTT of patient 4. For example,
IMD 10 may determine a difference between current values of each of
Z, StO.sub.2, and PTT and the corresponding baseline values of
patient 4. IMD 10 then may determine a weighted value for each of
the differences between the current values and the corresponding
baseline values. In some examples, IMD 10 may assign weights to the
difference values based on factors such as a medical history of
patient 4, which may include one or more of the medical history
events described above with respect to examples in which a
clinician manually modifies one or more of the weights. For
example, patient 4 may have a medical history of becoming
congested, which may indicate that patient 4 is prone to becoming
congested in the future. Or, population-based data may indicate
that patients having a same or similar profile of baseline values
as patient 4 may be particularly likely to become congested (or
inadequately perfused or vasoconstricted/vasodilated). In some
examples, weights assigned by IMD 10 to the difference values may
have negative values, such as if a medical history of patient 4 or
population-based data indicate that patient 4 is unlikely to become
congested (or inadequately perfused or
vasoconstricted/vasodilated). IMD 10 then may combine the weighted
values of the differences between the current values and the
baseline values, to arrive at a current diagnostic score for
patient 4.
[0054] In some examples, IMD 10 may compare the current diagnostic
score to the baseline diagnostic score of patient 4, the latter of
which may have been determined during a prior iteration of a method
in which IMD 10 determined a heart failure status of patient 4. IMD
10 then may determine an updated heart failure status of patient 4
based on the comparison of the baseline diagnostic score to the
current diagnostic score, and transmit the updated heart failure
status to a remote computer (e.g., external device 12). External
device 12, or another remote computer, then may transmit
instructions for a medical intervention (e.g., a change in a drug
regimen, or instructions to schedule a clinician visit or seek
medical attention), to an interface of a user device located with
patient 4.
[0055] In some examples, the baseline diagnostic score of patient 4
may be updated, in a substantially similar manner as described
above with respect to the threshold values. For example, the
baseline diagnostic score of patient 4 may be updated after patient
4 experiences an acute decompensation or hospitalization event,
which may indicate that one or more parameters of a heart failure
condition of patient 4 has progressed or otherwise changed. In some
examples, the baseline diagnostic score of patient 4 may be updated
at the expiration of a time period (e.g., weekly, monthly, or
yearly following implantation of IMD 10). Such updates to the
baseline diagnostic score of patient 4 may be performed
automatically by processing circuitry of IMD 10, or manually by a
clinician.
[0056] As described above, the operating parameters of IMD 10
readily may be customized to meet the needs of patient 4, such as
by setting values of baselines, thresholds, and evidence levels
based on the individual attributes of patient 4. The extent and
ease of customizability of IMD 10 may provide numerous benefits.
For example, customizability of IMD 10 to reflect a heart failure
condition of patient 4 helps ensure that appropriate drug therapies
are prescribed for patient 4, thereby reducing a likelihood of
human error in prescribing treatment. In addition, in examples in
which IMD 10 selects one or more of the baseline values, threshold
values, or evidence level values for patient 4, burdens on the
clinician's time may be reduced, which may reduce the time needed
for an office visit and promote efficient treatment. Moreover, as
discussed above, IMD 10 enables modification of heart failure
treatment for patient 4 in between clinician visits, which may help
avoid acute decompensation and thus lead to better clinical
outcomes, such as improved quality of life for patient 4 or reduced
medical expenses.
[0057] External device 12 may be used to program commands or
operating parameters into IMD 10 for controlling its functioning
(e.g., when configured as a programmer for IMD 10). In some
examples, external device 12 may be used to interrogate IMD 10 to
retrieve data, including device operational data as well as
physiological data accumulated in IMD memory. Such interrogation
may occur automatically according to a schedule, or may occur in
response to a remote or local user command. Programmers, external
monitors, and consumer devices are examples of external devices 12
that may be used to interrogate IMD 10. Examples of communication
techniques used by IMD 10 and external device 12 include
radiofrequency (RF) telemetry, which may be an RF link established
via Bluetooth, WiFi, or medical implant communication service
(MICS). In some examples, external device 12 may include a user
interface configured to allow a clinician to remotely interact with
IMD 10.
[0058] Medical system 2 is an example of a medical device system
configured to monitor a heart failure status of patient 4 and
facilitate updates to heart-failure treatment of patient 4 as
needed between clinician visits. The techniques described herein
may be performed by processing circuitry of a device of medical
system 2, such as processing circuitry of IMD 10. Additionally, or
alternatively, the techniques described herein may be performed, in
whole or in part, by processing circuitry of external device 12,
and/or by processing circuitry of one or more other implanted or
external devices or servers not shown. Examples of the one or more
other implanted or external devices may include a transvenous,
subcutaneous, or extravascular pacemaker or implantable
cardioverter-defibrillator (ICD), a blood analyzer, an external
monitor, or a drug pump. The communication circuitry of each of the
devices of system 2 allows the devices to communicate with one
another. In addition, although the optical sensors and electrodes
are described herein as being positioned on a housing of IMD 10, in
other examples, such optical sensors and/or electrodes may be
positioned on a housing of another device implanted in or external
to patient 4, such as a transvenous, subcutaneous, or extravascular
pacemaker or ICD, or coupled to such a device by one or more leads.
For example, in cases in which patient 4 has an implanted pacemaker
or ICD, the techniques described herein may include sensing signals
for determining Z with electrodes on the pacemaker or ICD. In such
examples, electrodes or one or more optical sensors for detecting
signals associated with StO.sub.2 and PTT may be positioned on one
or more external monitoring devices (e.g., a wearable monitor). In
such examples, one or more of the pacemaker/ICD and the one or more
external monitoring devices may include processing circuitry
configured to receive signals from the electrodes or optical
sensors on the respective devices and/or communication circuitry
configured to transmit the signals from the electrodes or optical
sensors to another device (e.g., external device 12) or server.
[0059] In some examples, medical system 2 may be configured to
monitor one or more parameters in addition to or instead of any of
Z, StO.sub.2, and PTT. For example, sensors on IMD 10 or one or
more other implanted or external devices may be configured to sense
signals associated with such parameters. Such one or more
parameters may be associated with physiological functions of
patient 4, such as kidney function, which may change when a heart
failure status of patient 4 changes. For example, one or more
implanted or external devices of medical system 2 (e.g., IMD 10)
may include one or more sensors configured to sense blood or tissue
levels of one or more compounds associated with kidney function of
patient 4, such as creatinine or blood urea nitrogen. In such
examples, techniques for determining a heart failure status of
patient 4 may include determining, by processing circuitry of IMD
10, external device 12, or one or more other implanted or external
devices or servers, a current value of the one or more parameters
in addition to or instead of any of Z, StO.sub.2, and PTT,
comparing such a current value to a corresponding baseline, and
using the comparison in determining the heart failure status of
patient 4. In some examples, such one or more parameters may not be
directly associated with changes in a heart failure status, but may
provide other information about the health of patient 4, such as
activity levels or sleep patterns.
[0060] FIGS. 2-4B illustrate various aspects and example
arrangements of IMD 10 of FIG. 1. For example, FIG. 2 conceptually
illustrates an example physical configuration of IMD 10. FIG. 3 is
a block diagram illustrating an example functional configuration of
IMD 10. FIGS. 4A and 4B illustrate additional views of an example
physical and functional configuration of IMD 10. It should be
understood that any of the examples of IMD 10 described below with
respect to FIGS. 2-4B may be used to implement the techniques
described herein for determining a heart failure status of patient
4.
[0061] FIG. 2 is a conceptual drawing illustrating an example
configuration of IMD 10 of FIG. 1. In the example shown in FIG. 2,
IMD 10 may comprise a leadless, subcutaneously-implantable
monitoring device having housing 14, proximal electrode 16A, and
distal electrode 16B. Housing 14 may further comprise first major
surface 18, second major surface 20, proximal end 22, and distal
end 24. In some examples, IMD 10 may include one or more additional
electrodes 16C, 16D positioned on one or both of major surfaces
18,20 of IMD 10. Housing 14 encloses electronic circuitry located
inside the IMD 10, and protects the circuitry contained therein
from fluids such as body fluids. In some examples, electrical
feedthroughs provide electrical connection of electrodes 16A-16D,
and antenna 26, to circuitry within housing 14. In some examples,
electrode 16B may be formed from an uninsulated portion of
conductive housing 14.
[0062] In the example shown in FIG. 2, IMD 10 is defined by a
length L, a width W, and thickness or depth D. In this example, IMD
10 is in the form of an elongated rectangular prism in which length
L is significantly greater than width W, and in which width W is
greater than depth D. However, other configurations of IMD 10 are
contemplated, such as those in which the relative proportions of
length L, width W, and depth D vary from those described and shown
in FIG. 2. In some examples, the geometry of the IMD 10, such as
the width W being greater than the depth D, may be selected to
allow IMD 10 to be inserted under the skin of the patient using a
minimally invasive procedure and to remain in the desired
orientation during insertion. In addition, IMD 10 may include
radial asymmetries (e.g., the rectangular shape) along a
longitudinal axis of IMD 10, which may help maintain the device in
a desired orientation following implantation.
[0063] In some examples, a spacing between proximal electrode 16A
and distal electrode 16B may range from about 30-55 mm, about 35-55
mm, or about 40-55 mm, or more generally from about 25-60 mm.
Overall, IMD 10 may have a length L of about 20-30 mm, about 40-60
mm, or about 45-60 mm. In some examples, the width W of major
surface 18 may range from about 3-10 mm, and may be any single
width or range of widths between about 3-10 mm. In some examples, a
depth D of IMD 10 may range from about 2-9 mm. In other examples,
the depth D of IMD 10 may range from about 2-5 mm, and may be any
single or range of depths from about 2-9 mm. In any such examples,
IMD 10 is sufficiently compact to be implanted within the
subcutaneous space of patient 4 in the region of a pectoral
muscle.
[0064] IMD 10, according to an example of the present disclosure,
may have a geometry and size designed for ease of implant and
patient comfort. Examples of IMD 10 described in this disclosure
may have a volume of 3 cubic centimeters (cm.sup.3) or less, 1.5
cm.sup.3 or less, or any volume therebetween. In addition, in the
example shown in FIG. 2, proximal end 22 and distal end 24 are
rounded to reduce discomfort and irritation to surrounding tissue
once implanted under the skin of patient 4. In some examples, a
configuration of IMD 10, including instrument and method for
inserting IMD 10 is described, for example, in U.S. Patent
Publication No. 2014/0276928, incorporated herein by reference in
its entirety. In some examples, a configuration of IMD 10 is
described, for example, in U.S. Patent Publication No.
2016/0310031, incorporated herein by reference in its entirety.
[0065] In the example shown in FIG. 2, first major surface 18 of
IMD 10 faces outward towards the skin, when IMD 10 is inserted
within patient 4, whereas second major surface 20 is faces inward
toward musculature of patient 4. Thus, first and second major
surfaces 18, 20 may face in directions along a sagittal axis of
patient 4 (see FIG. 1), and this orientation may be maintained upon
implantation due to the dimensions of IMD 10.
[0066] Proximal electrode 16A and distal electrode 16B may be used
to sense cardiac EGM signals (e.g., ECG signals) when IMD 10 is
implanted subcutaneously in patient 4. In the techniques described
herein, processing circuitry of IMD 10 may determine a PTT value
based in part on cardiac ECG signals, as further described below.
In some examples, processing circuitry of IMD 10 also may determine
whether cardiac ECG signals of patient 4 are indicative of
arrhythmia or other abnormalities, which processing circuitry of
IMD 10 may evaluate in determining whether a heart failure status
of patient 4 has changed. The cardiac ECG signals may be stored in
a memory of the IMD 10, and data derived from the cardiac ECG
signals may be transmitted via integrated antenna 26 to another
medical device, such as external device 12. In some examples, one
or both of electrodes 16A and 16B also may be used to detect
subcutaneous impedance value Z for assessing a congestion status of
patient 4, and/or may be used by communication circuitry of IMD 10
for TCC communication with external device 12.
[0067] In the example shown in FIG. 2, proximal electrode 16A is in
close proximity to proximal end 22, and distal electrode 16B is in
close proximity to distal end 24 of IMD 10. In this example, distal
electrode 16B is not limited to a flattened, outward facing
surface, but may extend from first major surface 18, around rounded
edges 28 or end surface 30, and onto the second major surface 20 in
a three-dimensional curved configuration. As illustrated, proximal
electrode 16A is located on first major surface 18 and is
substantially flat and outward facing. However, in other examples
not shown here, proximal electrode 16A and distal electrode 16B
both may be configured like proximal electrode 16A shown in FIG. 2,
or both may be configured like distal electrode 16B shown in FIG.
2. In some examples, additional electrodes 16C and 16D may be
positioned on one or both of first major surface 18 and second
major surface 20, such that a total of four electrodes are included
on IMD 10. Any of electrodes 16A-16D may be formed of a
biocompatible conductive material. For example, any of electrodes
16A-16D may be formed from any of stainless steel, titanium,
platinum, iridium, or alloys thereof. In addition, electrodes of
IMD 10 may be coated with a material such as titanium nitride or
fractal titanium nitride, although other suitable materials and
coatings for such electrodes may be used.
[0068] In the example shown in FIG. 2, proximal end 22 of IMD 10
includes header assembly 32 having one or more of proximal
electrode 16A, integrated antenna 26, anti-migration projections
34, and suture hole 36. Integrated antenna 26 is located on the
same major surface (e.g., first major surface 18) as proximal
electrode 16A, and may be an integral part of header assembly 32.
In other examples, integrated antenna 26 may be formed on the major
surface opposite from proximal electrode 16A, or, in still other
examples, may be incorporated within housing 14 of IMD 10. Antenna
26 may be configured to transmit or receive electromagnetic signals
for communication. For example, antenna 26 may be configured to
transmit to or receive signals from a programmer via inductive
coupling, electromagnetic coupling, tissue conductance, Near Field
Communication (NFC), Radio Frequency Identification (RFID),
Bluetooth, WiFi, or other proprietary or non-proprietary wireless
telemetry communication schemes. Antenna 26 may be coupled to
communication circuitry of IMD 10, which may drive antenna 26 to
transmit signals to external device 12, and may transmit signals
received from external device 12 to processing circuitry of IMD 10
via communication circuitry.
[0069] IMD 10 may include several features for retaining IMD 10 in
position once subcutaneously implanted in patient 4. For example,
as shown in FIG. 2, housing 14 may include anti-migration
projections 34 positioned adjacent integrated antenna 26.
Anti-migration projections 34 may comprise a plurality of bumps or
protrusions extending away from first major surface 18, and may
help prevent longitudinal movement of IMD 10 after implantation in
patient 4. In other examples, anti-migration projections 34 may be
located on the opposite major surface as proximal electrode 16A
and/or integrated antenna 26. In addition, in the example shown in
FIG. 2 header assembly 32 includes suture hole 36, which provides
another means of securing IMD 10 to the patient to prevent movement
following insertion. In the example shown, suture hole 36 is
located adjacent to proximal electrode 16A. In some examples,
header assembly 32 may comprise a molded header assembly made from
a polymeric or plastic material, which may be integrated or
separable from the main portion of IMD 10.
[0070] Electrodes 16A and 16B may be used to sense cardiac ECG
signals for PTT value determination, as described above. Additional
electrodes 16C and 16D may be used to sense subcutaneous tissue
impedance (e.g., either for measuring Z and/or for measuring PTT),
in addition to or instead of electrodes 16A, 16B, in some examples.
In some cases, it may be advantageous to use separate electrode
pairs for determining the current Z and PTT values of patient 4.
For example, using separate electrodes 16A, 16B for impedance
measurement and electrodes 16C, 16D for ECG sensing may help reduce
a likelihood that a signal generated for determining a Z value may
interfere with signals sensed by electrodes 16C, 16D during the
sensing of cardiac ECG signals. In addition, using separate
electrode pairs for determining current Z and PTT values of patient
4 may better enable adaptation of one or more aspects of electrodes
16A-16D (e.g., size or spacing) to the assigned function of each
electrode.
[0071] In some examples, processing circuitry of IMD 10 may
determine a Z value of patient 4 based on signals received from at
least two of electrodes 16A-16D. For example, processing circuitry
of IMD 10 may generate one of a current or voltage signal, deliver
the signal via a selected two or more of electrodes 16A-16D, and
measure the resulting other of current or voltage. Processing
circuitry of IMD 10 may determine an impedance signal based on the
delivered current or voltage and the measured voltage or
current.
[0072] In some examples, processing circuitry of IMD 10 may
determine a PTT value of patient 4 based on the sensed ECG signal
from electrodes 16A, 16B and the current value of Z based on
signals received from electrodes 16C and 16D. For example, the
processing circuitry of IMD 10 may receive the ECG signal from
electrodes 16A, 16B, and identify one or more features of a cardiac
cycle within the ECG signal. The processing circuitry may identify
an R wave within a cardiac cycle, and associate a first time (T1)
with the occurrence of the R wave. Next, the processing circuitry
may identify a fluctuation in the subcutaneous tissue impedance
signal occurring after T1, and associate a second time (T2) with
the fluctuation, which may represent the passing of blood ejected
during the observed cardiac cycle through the portion of the
vasculature near electrodes 16C, 16D. By subtracting T2 from T1,
processing circuitry of IMD 10 then may determine a PTT value
(e.g., in milliseconds) of patient 4. To enable IMD 10 to
accurately identify fluctuations in PTT values of patient 4, it may
be beneficial for a clinician to implant IMD 10 substantially as
shown in FIG. 1, with at least a portion of IMD 10 positioned at or
inferior to heart 6. In this way, IMD 10 may be positioned at a
sufficient circulatory distance from heart 6 to detect even small
fluctuations in PTT, which may help IMD 10 to accurately assess a
heart failure status of patient 4.
[0073] In some other examples, techniques for determining PTT may
include using light emitter 38 to emit light at one or more
wavelengths, e.g., one or more visible (VIS) wavelengths (e.g.,
approximately 600 nanometers (nm)) and/or one or more near-infrared
(NIR) wavelengths (e.g., approximately 850-890 nm) in addition to
the sensed ECG signal from electrodes 16A, 16B. In such examples,
processing circuitry of IMD 10 controls light emitter 38 to emit
light at the one or more wavelengths, such as a NIR or VIS
wavelength, and concurrently monitor the sensed ECG signal. The
processing circuitry may identify an R wave within a cardiac cycle
and associate a first time (T1) with the occurrence of the R wave.
Next, the processing circuitry may identify a fluctuation in the
light detected by light detectors 40A, 40B occurring after T1, and
associate a second time (T2) with the fluctuation, which may
represent the passing of blood ejected during the observed cardiac
cycle through the portion of the vasculature near light detectors
40A, 40B. By subtracting T2 from T1, processing circuitry of IMD 10
then may determine a PTT value (e.g., in milliseconds) of patient
4.
[0074] In the example shown in FIG. 2, IMD 10 includes a light
emitter 38, a proximal light detector 40A, and a distal light
detector 40B positioned on housing 14 of IMD 10. Light detector 40A
may be positioned at a distance S from light emitter 38, and a
distal light detector 40B positioned at a distance S+N from light
emitter 38. In other examples, IMD 10 may include only one of light
detectors 40A, 40B, or may include additional light emitters and/or
additional light detectors. Collectively, light emitter 38 and
light detectors 40A, 40B may comprise an optical sensor, which may
be used in the techniques described herein to determine StO.sub.2
or PTT values of patient 4. Although light emitter 38 and light
detectors 40A, 40B are described herein as being positioned on
housing 14 of IMD 10, in other examples, one or more of light
emitter 38 and light detectors 40A, 40B may be positioned, on a
housing of another type of IMD within patient 4, such as a
transvenous, subcutaneous, or extravascular pacemaker or ICD, or
connected to such a device via a lead. Light emitter 38 includes a
light source, such as an LED, that may emit light at one or more
wavelengths within the (VIS) and/or (NIR) spectra. For example,
light emitter 38 may emit light at one or more of about 660 (nm),
720 nm, 760 nm, 800 nm, or at any other suitable wavelengths.
[0075] In some examples, techniques for determining StO.sub.2 may
include using light emitter 38 to emit light at one or more VIS
wavelengths (e.g., approximately 600 nm) and at one or more NIR
wavelengths (e.g., approximately 850-890 nm). The combination of
VIS and NIR wavelengths may help enable processing circuitry of IMD
10 to distinguish oxygenated hemoglobin from deoxygenated
hemoglobin in the tissue of patient 4, because oxygenated
hemoglobin absorbs more NIR light than VIS light, whereas
deoxygenated hemoglobin absorbs more VIS light than NIR light. By
comparing the amount of VIS light detected by light detectors 40A,
40B to the amount of NIR light detected by light detectors 40A,
40B, processing circuitry of IMD 10 may determine the relative
amounts of oxygenated and deoxygenated hemoglobin in the tissue of
patient 4. For example, if the amount of oxygenated hemoglobin in
the tissue of patient 4 decreases, the amount of VIS light detected
by light detectors 40A, 40B increases and the amount of NIR light
detected by light detectors 40A, 40B decreases. Similarly, if the
amount of oxygenated hemoglobin in the tissue of patient 4
increases, the amount of VIS light detected by light detectors 40A,
40B decreases and the amount of NIR light detected by light
detectors 40A, 40B increases.
[0076] As shown in FIG. 2, light emitter 38 may be positioned on
header assembly 32, although, in other examples, one or both of
light detectors 40A, 40B may additionally or alternatively be
positioned on header assembly 32. In some examples, light emitter
38 may be positioned on a medial section of IMD 10, such as part
way between proximal end 22 and distal end 24. Although light
emitter 38 and light detectors 40A, 40B are illustrated as being
positioned on first major surface 18, light emitter 38 and light
detectors 40A, 40B alternatively may be positioned on second major
surface 20. In some examples, IMD may be implanted such that light
emitter 38 and light detectors 40A, 40B face inward when IMD 10 is
implanted, toward the muscle of patient 4, which may help minimize
interference from background light coming from outside the body of
patient 4. Light detectors 40A, 40B may include a glass or sapphire
window, such as described below with respect to FIG. 4B, or may be
positioned beneath a portion of housing 14 of IMD 10 that is made
of glass or sapphire, or otherwise transparent or translucent.
[0077] Light emitter 38 may emit light into a target site of
patient 4 during a technique for determining an StO.sub.2 value of
patient 4. The target site may generally include the interstitial
space around IMD 10 when IMD 10 is implanted in patient 4. Light
emitter 38 may emit light directionally in that light emitter may
direct the signal to a side of IMD 10, such as when light emitter
38 is disposed on the side of IMD 10 that includes first major
surface 18. The target site may include the subcutaneous tissue
adjacent IMD 10 within patient 4. In one example, light emitter 38
may deliver 180-degree light signals, such as 180 degrees along a
dimension parallel to a longitudinal axis of IMD 10. In some
examples, a light signal may be a cloud of light generally directed
inward, toward the musculature and away from the skin of patient 4.
In some examples, the light signal may take the mean free path, as
the light signal may be non-directional once emitted from light
emitter 38.
[0078] Techniques for determining an StO.sub.2 value may be based
on the optical properties of blood-perfused tissue that change
depending upon the relative amounts of oxygenated and deoxygenated
hemoglobin in the microcirculation of tissue. These optical
properties are due, at least in part, to the different optical
absorption spectra of oxygenated and deoxygenated hemoglobin. Thus,
the oxygen saturation level of the patient's tissue may affect the
amount of light that is absorbed by blood within the tissue
adjacent IMD 10, and the amount of light that is reflected by the
tissue. Light detectors 40A, 40B each may receive light from light
emitter 38 that is reflected by the tissue, and generate electrical
signals indicating the intensities of the light detected by light
detectors 40A, 40B. Processing circuitry of IMD 10 then may
evaluate the electrical signals from light detectors 40A, 40B in
order to determine an StO.sub.2 value of patient 4.
[0079] In some examples, a difference between the electrical
signals generated by light detectors 40A, 40B may enhance an
accuracy of the StO.sub.2 value determined by IMD 10. For example,
because tissue absorbs some of the light emitted by light emitter
38, the intensity of the light reflected by tissue becomes
attenuated as the distance (and amount of tissue) between light
emitter 38 and light detectors 40A, 40B increases. Thus, because
light detector 40B is positioned further from light emitter 38 (at
distance S+N) than light detector 40A (at distance S), the
intensity of light detected by light detector 40B should be less
than the intensity of light detected by light detector 40A. Due to
the close proximity of detectors 40A, 40B to one another, the
difference between the intensity of light detected by detector 40A
and the intensity of light detected by detector 40B should be
attributable only to the difference in distance from light emitter
38. In some examples, processing circuitry of IMD 10 may use the
difference between the electrical signals generated by light
detectors 40A, 40B, in addition to the electrical signals
themselves, in determining an StO.sub.2 value of patient 4.
[0080] As noted above, light emitter 38 and one or both of light
detectors 40A, 40B also may be used in a technique for determining
a PTT value of patient 4. As with techniques for determining PTT in
which processing circuitry of IMD 10 receives a subcutaneous tissue
impedance signal from a plurality of electrodes 16A-16D, techniques
for determining PTT that include using an optical sensor include
identifying one or more features within a cardiac cycle of patient
4, and associating a first time T1 with an occurrence in the
cardiac cycle. Instead of determining a second time T2 based on an
impedance signal, however, IMD 10 may determine T2 by identifying a
fluctuation in the intensity and/or wavelength of light detected by
one or both of light detectors 40A, 40B occurring after T1, and
associate the second time (T2) with the fluctuation, which may
represent the passing of blood ejected during the cardiac cycle
through the portion of the vasculature near the light detectors
40A, 40B. By subtracting T2 from T1, processing circuitry of IMD 10
then may determine a PTT value (e.g., in milliseconds) of patient
4.
[0081] In some examples, IMD 10 may include one or more additional
sensors, such as one or more accelerometers (not shown). Such
accelerometers may be 3D accelerometers configured to generate
signals indicative of one or more types of movement of the patient,
such as gross body movement (e.g., activity) of the patient,
patient posture, movements associated with the beating of the
heart, or coughing, rales, or other respiration abnormalities. In
some examples, one or more of such accelerometers may be used, in
conjunction with light emitter 38 and optical detectors 40A, 40B,
to determine a ballistocardiogram (i.e., a measure of motion
corresponding to blood ejection at systole) that processing
circuitry of IMD 10 may use to determine PTT instead of or in
addition to an ECG signal from a pair of electrodes 16A-16D.
Additionally, or alternatively, one or more of the parameters
monitored by IMD 10 (i.e., Z, StO.sub.2, or PTT) may fluctuate in
response to changes in one or more such types of movement. For
example, changes in Z, StO.sub.2, or PTT values sometimes may be
attributable to increased patient activity (e.g., exercise or other
physical activity as compared to inactivity) or to changes in
patient posture, and not necessarily to changes in a heart failure
status caused by a progression of a heart failure condition. Thus,
in some methods of determining a heart failure status of patient 4,
it may be advantageous to account for such fluctuations when
determining whether a change in a parameter, such as Z, StO.sub.2,
or PTT, that exceeds a threshold is indicative of a change in a
corresponding one of a congestion status, a tissue perfusion
status, or a blood pressure status of patient 4.
[0082] In such examples, processing circuitry of IMD 10 may receive
one or more signals from one or more accelerometers of IMD 10, and
determine a value of one or more patient-activity parameters, such
as gross body movement. In this example, processing circuitry of
IMD 10 may cross-reference the determined patient-activity value
with values of one or more other parameters, such as a Z,
StO.sub.2, or PTT value. If the patient-activity value satisfies a
threshold, processing circuitry of IMD 10 may determine that a
change in a current a Z, StO.sub.2, or PTT value that otherwise may
indicate a change in a heart failure status does not indicate a
change in a congestion, tissue perfusion, or blood pressure status
of patient 4. In such instances, processing circuitry of patient 4
may designate the current value as an outlier and not use it in
determining a heart failure status of patient 4. In some examples,
processing circuitry of IMD 10 may cross-reference the determined
activity or posture values with different scaling factors to be
applied the Z, StO.sub.2, or PTT values prior to comparison to a
threshold, or to different threshold values to which to compare the
measured Z, StO.sub.2, or PTT values. Although processing circuitry
of IMD 10 is described above as being configured to receive signals
from one or more accelerometers, electrodes 16A-16D, light emitter
38, and/or light detectors 40A, 40B of IMD 10 and determine a value
of one or more parameters of patient 4 based on such signals, any
steps described herein as being carried out by processing circuitry
of IMD 10 may carried out by processing circuitry of one or more
devices. For example, processing circuitry of external device 12,
or any other suitable implantable or external device or server, may
be configured to receive signals from the one or more
accelerometers, electrodes 16A-16D, light emitter 38, and/or light
detectors 40A, 40B of IMD 10, such as via communication circuitry
of IMD 10.
[0083] FIG. 3 is a functional block diagram illustrating an example
configuration of IMD 10 of FIGS. 1 and 2. In the illustrated
example, IMD 10 includes processing circuitry 50 sensing circuitry
52, communication circuitry 54, memory 56, switching circuitry 58,
sensors 62, timing/control circuitry 64, in addition to
previously-described electrodes 16A-16D, one or more of which may
be disposed within housing 14 of IMD 10, and light emitter 38. In
some examples, memory 56 includes computer-readable instructions
that, when executed by processing circuitry 50, cause IMD 10 and
processing circuitry 50 to perform various functions attributed to
IMD 10 and processing circuitry 50 herein. Memory 56 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 media.
[0084] Processing circuitry 50 may include fixed function circuitry
and/or programmable processing circuitry. Processing circuitry 50
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,
processing circuitry 50 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 processing circuitry 50 herein may be
embodied as software, firmware, hardware or any combination
thereof.
[0085] Timing and control circuitry 64 may be embodied as hardware,
firmware, software, or any combination thereof. In some examples,
timing and control circuitry 64 may comprise a dedicated hardware
circuit, such as an ASIC, separate from other processing circuitry
50 components, such as a microprocessor, or a software module
executed by a component of processing circuitry 50 (e.g., a
microprocessor or ASIC). Timing and control circuitry 64 may
monitor the passage of time to determine when a monitoring period
has elapsed, and help control IMD 10 to measure current values of
Z, StO.sub.2, and PTT of patient 4. Timing and control circuitry 64
also may control IMD 10 to transmit a heart failure status of
patient 4 to external device 12, at the conclusion of a
corresponding interval.
[0086] In some examples, timing and control circuitry 64 may be
configured to associate current values of Z, StO.sub.2, and PTT
with a particular time of day, such as day time or night time, so
as to enable processing circuitry 50 to take into account a
circadian rhythm of patient 4 when determining congestion, tissue
perfusion, and/or blood pressure statuses of patient 4. For
example, one or more of the values of Z, StO.sub.2, and PTT values
of patient 4 generally may decrease when patient 4 is asleep (e.g.,
nighttime), and increase when patient 4 is awake (e.g., daytime).
Thus, IMD 10 may be configured to use different (e.g., lower)
baseline value and/or threshold values for a particular parameter
at times when patient 4 is likely to be asleep than when patient 4
is likely to be awake. In some examples in which IMD 10 includes
one or more accelerometers, processing circuitry 50 may
cross-reference a time of day indicated by timing and control
circuitry with accelerometer data, such as to confirm whether
patient 4 is asleep or awake as predicted based on the time of day.
In this manner, timing and control circuitry 64 may enhance the
ability of IMD 10 to accurately determine a heart failure status of
patient 4.
[0087] In addition to sensed physiological parameters of patient 4
(e.g., determined values of Z, StO.sub.2, and PTT), one or more
time intervals for timing the measurements of Z, StO.sub.2, and PTT
by processing circuitry 50 may be stored by memory 56 in stored
measurements/intervals 68. For example, the intervals 68 stored by
memory 56 may instruct processing circuitry 50 to measure current
values of Z, StO.sub.2, and PTT of patient 4 hourly, several times
daily, daily, or at any other appropriate interval. Stored
measurements/intervals 68 also may include intervals at which
processing circuitry may be configured to transmit a heart failure
status of patient 4 to external device 12, such as daily, weekly,
or at any other suitable interval. In some examples, processing
circuitry 50 may select intervals for measuring Z, StO.sub.2, and
PTT or for transmitting a heart failure status of patient 4 from
stored measurements/intervals 68. In other examples, a clinician
may select interval values depending upon the needs of patient 4,
such as by using an application on a tablet or other smart device,
which in some examples may be external device 12.
[0088] As illustrated in FIG. 3, memory 56 also may include one or
more tables 70 for storing baseline, threshold, and evidence level
values. As described above, in some examples, processing circuitry
50 of IMD 10 may be configured to determine baseline values of Z,
StO.sub.2, and PTT during a learning phase of IMD 10, which then
may be stored in tables 70. In addition, tables 70 may include
pre-programmed baseline values that a clinician may select for
patient 4 during setup of IMD 10, or baseline values that a
clinician may manually enter based on the clinician's assessments
of patient 4. Processing circuitry 50 also may be configured to
determine threshold values for deviations of current values of Z,
StO.sub.2, and PTT from the baseline values, and store the
threshold values in tables 70. In some examples, processing
circuitry 50 may determine such threshold values based, at least in
part, on baseline values selected for patient 4. In addition to the
baseline values, tables 70 may include threshold values that a
clinician may select for patient 4 during setup of IMD 10, or
threshold values that a clinician may manually enter based on the
clinician's assessments of patient 4. Tables 70 also may include
values for evidence levels that may be associated with certain
values of Z, StO.sub.2, or PTT that may be used by processing
circuitry 50 to determine a diagnostic score of patient 4. As
described above, a heart failure status may comprise a diagnostic
score of patient 4, which in some examples may be a composite
diagnostic score based on a combination of values of evidence
levels associated with one or more current values of Z, StO.sub.2,
and PTT of patient 4.
[0089] Sensing circuitry 52 and communication circuitry 54 may be
selectively coupled to electrodes 16A-16D via switching circuitry
58, as controlled by processing circuitry 50. Sensing circuitry 52
may monitor signals from electrodes 16A-16D in order to monitor
electrical activity of heart (e.g., to produce an ECG for PTT
determination), and/or subcutaneous tissue impedance Z (e.g., as a
measure of congestion or for PTT determination). Sensing circuitry
52 also may monitor signals from sensors 62, which may include
light detectors 40A, 40B, and any additional light detectors that
may be positioned on IMD 10. In some examples, sensing circuitry 52
may include one or more filters and amplifiers for filtering and
amplifying signals received from one or more of electrodes 16A-16D
and/or light detectors 40A, 40B.
[0090] In some examples, processing circuitry 50 also may include a
rectifier, filter and/or amplifier, a sense amplifier, comparator,
and/or analog-to-digital converter. Upon receiving signals from
electrodes 16A-16D and light detectors 40A, 40B via sensing
circuitry 52, processing circuitry 50 may determine current values
for each of Z, StO.sub.2, and PTT for patient 4. Processing
circuitry then may compare the current values of Z, StO.sub.2, and
PTT to the baseline levels stored in tables 70, and determine
whether differences between the current values and the
corresponding baseline levels satisfy corresponding thresholds
stored in tables 70.
[0091] The threshold values stored in tables 70 may be associated
with changes in certain parameters of a heart failure status of
patient 4. For example, a threshold value corresponding to the Z
value may be associated with a change in a congestion status of
patient 4, whereas a threshold value corresponding to the StO.sub.2
value may be associated with a change in a tissue perfusion status
of patient 4, and a threshold value corresponding to the PTT value
may be associated with a change in a vascular resistance or blood
pressure status of patient 4. In some examples, processing
circuitry 50 may identify evidence level values associated with the
current values of Z, StO.sub.2, and PTT of patient 4, and determine
a diagnostic score associated with a combination of the evidence
levels. Processing circuitry 50 may store the determined current
values, associated evidence levels, and diagnostic scores in stored
measurements/intervals 68 of memory 56, along with an indication of
a date and time of the measurements. Simultaneously or thereafter,
processing circuitry 50 may transmit, via communication circuitry
54, the diagnostic score and/or one or more additional indicators
of a heart failure status of patient 4 to external device 12.
[0092] Communication circuitry 54 may include any suitable
hardware, firmware, software or any combination thereof for
communicating with another device, such as external device 12 or
another IMD or sensor, such as a pressure sensing device. Under the
control of processing circuitry 50, communication circuitry 54 may
receive downlink telemetry from, as well as send uplink telemetry
to, external device 12 or another device with the aid of an
internal or external antenna, e.g., antenna 26. In some examples,
communication circuitry 54 may communicate with external device 12.
In addition, processing circuitry 50 may communicate with a
networked computing device via external device (e.g., external
device 12) and a computer network, such as the Medtronic
CareLink.RTM. Network developed by Medtronic, plc, of Dublin,
Ireland.
[0093] A clinician or other user may retrieve data from IMD 10
using external device 12, or by using another local or networked
computing device configured to communicate with processing
circuitry 50 via communication circuitry 54. The clinician may also
program parameters of IMD 10 using external device 12 or another
local or networked computing device. In some examples, the
clinician may select baseline values, threshold values, times of
day for Z, StO.sub.2, and PTT measurements, or a number of
measurements to be completed during a period, e.g., day, and may
program evidence levels to be associated with the parameters of Z,
StO.sub.2, and PTT.
[0094] The various components of IMD 10 may be coupled a power
source, which may include a rechargeable or non-rechargeable
battery positioned within housing 14 of IMD 10. A non-rechargeable
battery may be selected to last for several years, while a
rechargeable battery may be inductively charged from an external
device, e.g., on a daily or weekly basis.
[0095] FIGS. 4A and 4B illustrate two additional example IMDs that
may be substantially similar to IMD 10 of FIGS. 1-3, but which may
include one or more additional features. The components of FIGS. 4A
and 4B may not necessarily be drawn to scale, but instead may be
enlarged to show detail. FIG. 4A is a block diagram of a top view
of an example configuration of an IMD 10A. FIG. 4B is a block
diagram of a side view of example IMD 10B, which may include an
insulative layer as described below.
[0096] FIG. 4A is a conceptual drawing illustrating another example
IMD 10A that may be substantially similar to IMD 10 of FIG. 1. In
addition to the components illustrated in FIGS. 1-3, the example of
IMD 10 illustrated in FIG. 4A also may include a body portion 72
and an attachment plate 74. Attachment plate 74 may be configured
to mechanically couple header 32 to body portion 72 of IMD 10A.
Body portion 72 of IMD 10A may be configured to house one or more
of the internal components of IMD 10 illustrated in FIG. 3, such as
one or more of processing circuitry 50, sensing circuitry 52,
communication circuitry 54, memory 56, switching circuitry 58,
internal components of sensors 62, and timing control circuitry 64.
In some examples, body portion 72 may be formed of one or more of
titanium, ceramic, or any other suitable biocompatible
materials.
[0097] FIG. 4B is a conceptual drawing illustrating another example
IMD 10B that may include components substantially similar to IMD 10
of FIG. 1. In addition to the components illustrated in FIGS. 1-3,
the example of IMD 10B illustrated in FIG. 4B also may include a
wafer-scale insulative cover 76, which may help insulate electrical
signals passing between electrodes 16A-16D and/or optical detectors
40A, 40B on housing 14B and processing circuitry 50. In some
examples, insulative cover 76 may be positioned over an open
housing 14 to form the housing for the components of IMD 10B. One
or more components of IMD 10B (e.g., antenna 26, light emitter 38,
light detectors 40A, 40B, processing circuitry 50, sensing
circuitry 52, communication circuitry 54, switching circuitry 58,
and/or timing/control circuitry 64) may be formed on a bottom side
of insulative cover 76, such as by using flip-chip technology.
Insulative cover 76 may be flipped onto a housing 14B. When flipped
and placed onto housing 14B, the components of IMD 10B formed on
the bottom side of insulative cover 76 may be positioned in a gap
78 defined by housing 14B.
[0098] Insulative cover 76 may be configured so as not to interfere
with the operation of IMD 10B. For example, one or more of
electrodes 16A-16D may be formed or placed above or on top of
insulative cover 76, and electrically connected to switching
circuitry 58 through one or more vias (not shown) formed through
insulative cover 76. In addition, to enable IMD to determine values
of StO.sub.2 and PTT, at least a portion of insulative cover 76 may
transparent to the NIR or visible wavelengths emitted by light
emitter 38 and detected by light detectors 40A, 40B, which in some
examples may be positioned on a bottom side of insulative cover 76
as described above.
[0099] In some examples, light emitter 38 may include an optical
filter between light emitter 38 and insulative cover 76, which may
limit the spectrum of emitted light to be within a narrow band.
Similarly, light detectors 40A, 40B may include optical filters
between light detectors 40A, 40B and insulative cover 76, so that
light detectors 40A, 40B detects light from a narrow spectrum,
generally at longer wavelengths than the emitted spectrum. Other
optical elements that may be included in the IMD 10B may include
index matching layers, antireflective coatings, or optical
barriers, which may be configured to block light emitted sideways
by the light emitter 38 from reaching light detector 40.
[0100] Insulative cover 76 may be formed of sapphire (i.e.,
corundum), glass, parylene, and/or any other suitable insulating
material. Sapphire may be greater than 80% transmissive for
wavelengths in the range of about 300 nm to about 4000 nm, and may
have a relatively flat profile. In the case of variation, different
transmissions at different wavelengths may be compensated for, such
as by using a ratiometric approach. In some examples, insulative
cover 76 may have a thickness of about 300 micrometers to about 600
micrometers. Housing 14B may be formed from titanium or any other
suitable material (e.g., a biocompatible material), and may have a
thickness of about 200 micrometers to about 500 micrometers. These
materials and dimensions are examples only, and other materials and
other thicknesses are possible for devices of this disclosure.
[0101] FIG. 5 is a functional block diagram illustrating an example
system that includes an access point 90, a network 92, external
computing devices, such as a server 94, and one or more other
computing devices 100A-100N, which may be coupled to IMD 10,
sensing device 12, and external device 12 via network 92. In this
example, IMD 10 may use communication module 54 to communicate with
external device 12 via a first wireless connection, and to
communication with an access point 90 via a second wireless
connection. In the example of FIG. 5, access point 90, external
device 12, server 94, and computing devices 100A-100N are
interconnected and may communicate with each other through network
92.
[0102] Access point 90 may comprise a device that connects to
network 92 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 90 may be coupled to network 92
through different forms of connections, including wired or wireless
connections. In some examples, access point 90 may be a user
device, such as a tablet or smartphone, that may be co-located with
the patient. As discussed above, IMD 10 may be configured to
transmit data, such as current values and heart failure statuses,
to external device 12. In addition, access point 90 may interrogate
IMD 10, such as periodically or in response to a command from the
patient or network 92, in order to retrieve current values or heart
failure statuses determined by processing circuitry 50 of IMD 10,
or other operational or patient data from IMD 10. Access point 90
may then communicate the retrieved data to server 94 via network
92.
[0103] In some cases, server 94 may be configured to provide a
secure storage site for data that has been collected from IMD 10,
and/or external device 12. In some cases, server 94 may assemble
data in web pages or other documents for viewing by trained
professionals, such as clinicians, via computing devices 100A-100N.
One or more aspects of the illustrated system of FIG. 5 may be
implemented with general network technology and functionality,
which may be similar to that provided by the Medtronic
CareLink.RTM. Network developed by Medtronic plc, of Dublin,
Ireland.
[0104] In some examples, one or more of computing devices 100A-100N
(e.g., device 100A) may be a tablet or other smart device located
with a clinician, by which the clinician may program, receive
alerts from, and/or interrogate IMD 10. For example, the clinician
may access patient 4's Z, StO.sub.2, and PTT measurements through
device 100A, such as when patient 4 is in in between clinician
visits, to check on a heart failure status of patient 4 as desired.
In some examples, the clinician may enter instructions for a
medical intervention for patient 4 into an app in device 100A, such
as based on a heart failure status of patient 4 determined by IMD
10, or based on other patient data known to the clinician. Device
100A then may transmit the instructions for medical intervention to
another of computing devices 100A-100N (e.g., device 100B) located
with patient 4 or a caregiver of patient 4. For example, such
instructions for medical intervention may include an instruction to
change a drug dosage, timing, or selection, to schedule a visit
with the clinician, or to seek medical attention. In further
examples, device 100B may generate an alert to patient 4 based on a
heart failure status of patient 4 determined by IMD 10, which may
enable patient 4 proactively to seek medical attention prior to
receiving instructions for a medical intervention. In this manner,
patient 4 may be empowered to take action, as needed, to address
his or her heart failure status, which may help improve clinical
outcomes for patient 4.
[0105] FIGS. 6-12 are flow diagrams illustrating various techniques
related to determining a heart failure status of a patient based on
a comparison of current Z, StO.sub.2, and PTT values of the patient
to corresponding baseline values, in accordance with examples of
this disclosure. As described herein, the techniques illustrated
FIGS. 6-12 may be employed using one or more components of system
2, which have been described above with respect to FIGS. 1-5.
Although described as being performed by IMD 10, the techniques of
FIGS. 6-12 may be performed, in whole or in part, by processing
circuitry and memory of other devices of a medical device system,
as described herein. For example, although processing circuitry 50
of IMD is described as carrying out most of the example techniques
illustrated in FIGS. 6-9 for the sake of clarity, in other
examples, one or more devices (e.g., external device 12 or other
external device or server) or a clinician may carry out one or more
steps attributed below to processing circuitry 50 of IMD 10.
[0106] FIG. 6 is a flow diagram illustrating an example technique
for determining, by processing circuitry 50 of IMD 10, a heart
failure status of patient 4 based on a comparison of current tissue
oxygen saturation, impedance, and pulse transit time values (i.e.,
Z, StO.sub.2, and PTT) of patient 4 to corresponding baseline
values stored in tables 70 of memory 56, and transmitting the heart
failure status to remote device 12. According to the example of
FIG. 6, IMD 10 may determine baseline Z, StO.sub.2, and PTT values
for patient 4 (110). In some examples, IMD 10 may determine the
baseline values during a learning phase of IMD 10 following
implantation of IMD 10 into patient 4, as discussed above with
respect to FIG. 1. Such a learning phase may take place after
implantation of IMD 10 at a time that a heart failure condition of
patient 4 is stable (e.g., compensated).
[0107] During the learning phase, IMD 10 periodically may determine
current values of Z, StO.sub.2, and PTT of patient 4 based on
signals received from one or more of electrodes 16A-16D, light
emitter 38, and light detectors 40A, 40B and store the values in
stored measurements/intervals 68. IMD 10 then may analyze the
collected values of Z, StO.sub.2, and PTT to determine the baseline
values for patient 4. In some examples, IMD 10 may reject any
outlier values of Z, StO.sub.2, and PTT, and average the remaining
measurements, although other methods of data analysis may be used
to determine the baseline values from the collected values. In
other examples, a clinician may determine baseline values for
patient 4 by selecting baseline values stored in tables 70 of IMD
10 may as part of a start-up phase of treatment following the
implantation of IMD 10 within patient 4. In some examples, IMD 10
also may determine threshold values for each of the baseline Z,
StO.sub.2, and PTT values for patient 4. For example, processing
circuitry 50 may determine the threshold values for patient 4 based
on the determined baseline values for patient 4 by selecting the
threshold values from tables 70. In other examples, a clinician may
select threshold values for patient 4, which IMD then may associate
with the baseline values of Z, StO.sub.2, and PTT for patient 4 in
tables 70.
[0108] After IMD 10 has determined baseline and/or threshold values
of Z, StO.sub.2, and PTT for patient 4, such as at the conclusion
of a learning phase of IMD 10, IMD 10 may begin determining current
values of Z, StO.sub.2, and PTT for patient 4 (112). For example,
processing circuitry 50 of IMD 10 may receive signals from one or
more of electrodes 16A-16D, light emitter 38, and light detectors
40A, 40B, and determine current values of Z, StO.sub.2, and PTT
based on these signals, as described above with respect to FIGS.
1-3. Next, processing circuitry 50 of IMD 10 may compare the
current Z, StO.sub.2, and PTT values of patient 4 to corresponding
baseline values of patient 4 stored in tables 70, and determine a
difference between each of the current values of Z, StO.sub.2, and
PTT and the corresponding baseline values (114). In some examples,
processing circuitry 50 also may determine whether a difference
between one or more of the current values and the corresponding
baseline values satisfies a threshold value.
[0109] Based on the differences between the current values and the
baseline values determined at (114) and/or the determination of
whether one or more of the differences satisfy a threshold value,
processing circuitry 50 then determines a heart failure status of
patient 4 (116). As described herein, determining a heart failure
status may comprise determining a change in heart failure status of
the patient, e.g., whether a change in status is sufficient to
indicate acute decompensation.
[0110] In some examples, a threshold change value for a given
parameter may be an absolute value of a percentage of the baseline
value. For example, if a baseline value of Z=X, then a threshold
value of Z may be X.+-.0.2X. In other examples, one or more of Z,
StO.sub.2, and PTT may be associated with multiple threshold values
that correspond to different percentages of the baseline values,
which may take into account differences in significance between
values that exceed a baseline value and values that are less than a
baseline value. For example, if a baseline value of Z=X, then
threshold values of Z may be X+0.2X and X-0.1X, where values of Z
that are less than X have relatively greater significance than
values of Z that are greater than X. In any such examples, the
threshold values may be based on deviations from corresponding
baseline values, such as standard deviations or any other suitable
statistical functions.
[0111] IMD 10 may repeat steps 112-116 to periodically determine
updated heart failure statuses of patient 4 such as daily, weekly,
monthly, or at any other suitable period. In some examples, the
heart failure status of patient 4 may comprise a diagnostic score
that indicates a likelihood that patient 4 may require
hospitalization within a certain period of time, based on changes
in the congestion, perfusion, and vascular/blood pressure statuses
of patient 4. For example, processing circuitry 50 may determine a
diagnostic score of patient 4 based on a combination of values of
one or more evidence levels associated with the current values of
Z, StO.sub.2, and PTT. In general, evidence levels associated with
greater severities of congestion (as indicated by a relatively low
Z), inadequate peripheral perfusion (as indicated by a relatively
low StO.sub.2), and vasoconstriction (as indicated by a relatively
low PTT) may have higher values than evidence levels associated
with lesser severities of such parameters of heart failure. Thus, a
higher diagnostic score may indicate that patient 4 is at a greater
risk of acute decompensation and/or hospitalization or other
adverse medical events within a certain time period than a lower
diagnostic score. The determination by processing circuitry 50 of a
heart failure status of patient 4 based on diagnostic scores is
described further with respect to FIG. 8 below. Regardless of
whether the heart failure status of patient 4 determined by
processing circuitry 50 comprises a diagnostic score, processing
circuitry then transmits the heart failure status of patient 4 to a
remote computer, such as external device 12 (118).
[0112] FIG. 7 is a flow diagram illustrating an example technique
for determining the baseline or current values of tissue impedance,
tissue oxygen saturation, and pulse transit time described with
respect to FIG. 6. For example, processing circuitry 50 of IMD 10
may generate one of a current or voltage signal, deliver the signal
via a selected two or more of electrodes 16A-16D, and measure the
resulting other of current or voltage. Processing circuitry 50 then
may determine an impedance signal based on the delivered current or
voltage and the measured voltage or current. Based on the signal,
processing circuitry 50 determines an impedance value of
subcutaneous tissue of patient 4 in the region of implanted IMD 10
(120). The subcutaneous tissue impedance value may be used as
current value Z of patient 4, which is a measure of a congestion
status of patient 4 and pertains to a heart failure status of
patient 4. For example, a relatively low value of Z may indicate a
relatively high amount of blood and/or other fluid in the
subcutaneous tissue near IMD 10. Thus, if the current value of Z is
relatively low and/or is lower than a previous measured value of Z,
patient 4 may be experiencing an increase in congestion, which may
be reflected in a diagnostic score determined by processing
circuitry 50.
[0113] To determine a current value of PTT for patient 4,
processing circuitry 50 receives cardiac EGM signals (e.g., ECG
signals) from at least two of electrodes 16A-16D, and detects a
depolarization, such as a beginning of an R wave, within the
depolarization (122). In some examples, at least one of the
electrodes 16A-16D that transmit cardiac EGM signals to processing
circuitry 50 may be an electrode used to transmit a signal
indicative of a subcutaneous tissue impedance value to processing
circuitry 50, although in other examples, there may not be such
overlap in electrode usage. Processing circuitry 50 determines a
current StO.sub.2 value based on signals received by processing
circuitry 50 from light detectors 40A, 40B. In order to generate
such signals, processing circuitry 50 may control light emitter 38
to emit light at one or more wavelengths in the NIR and/or visible
spectra into the subcutaneous tissue adjacent IMD 10. A portion of
the emitted light is absorbed by the tissue of patient 4, and a
portion of the emitted light is reflected by the tissue and
received by light detectors 40A, 40B. Light detectors 40A, 40B then
generate electrical signals indicating the intensities of the
received light, which processing circuitry 50 evaluates in order to
determine a current StO.sub.2 value of patient 4 (124). Processing
circuitry 50 additionally receives signals from light detectors
40A, 40B, which may comprise electrical signals indicative of
intensities of light detected by light detectors 40A, 40B, and
monitors the signals for fluctuations corresponding to a pulse of
blood ejected during the observed cardiac cycle passing through the
portion of the vasculature near light detectors 40A, 40B. As
discussed above with respect to FIG. 2, processing circuitry 50 may
determine an amount of time between the detection of the cardiac
cycle by processing circuitry 50 and the time of associated blood
passing light detectors 40A, 40B (124), and identify the amount of
time as a current PTT value of patient 4 (126). In other examples,
such as those discussed above with respect to FIG. 2, processing
circuitry 50 may determine a current PTT value of patient 4 based
on an ECG and fluctuations in subcutaneous tissue impedance
detected by two or more of electrodes 16A-16D, instead of based on
an ECG and signals from optical detectors 40A, 40B.
[0114] In some examples, the current values of one or more of Z,
StO.sub.2, and PTT may exhibit random variability. In order to
account for such variability, a comparison of the current
diagnostic score to the baseline diagnostic score carried out by
processing circuitry 50 may include curve fitting and trend
analysis. For example, if processing circuitry 50 measures values
of Z, StO.sub.2, and PTT several times daily, processing circuitry
may accumulate such values over a period of time (e.g., over
several days or several weeks) and fit the accumulated values of
each of Z, StO.sub.2, and PTT to a corresponding trendline. Then,
processing circuitry 50 may use the trendlines to project
corresponding current values of Z, StO.sub.2, and PTT. In this
manner, processing circuitry 50 may account for random fluctuations
when determining current values of Z, StO.sub.2, and PTT as
described above, which may enhance the accuracy with which the
current values of Z, StO.sub.2, and PTT reflect the congestion,
tissue perfusion, and blood pressure statuses of patient 4.
[0115] FIG. 8 is a flow diagram illustrating an example technique
for determining, by processing circuitry 50 of IMD 10, a current
diagnostic score of patient 4, and determining an updated heart
failure status of patient 4 based on a comparison of the current
diagnostic score to a baseline diagnostic score. A comparison of a
current diagnostic score of patient 4 to a baseline diagnostic
score of patient 4 may provide additional information about changes
in a heart failure status of patient 4, and may further inform
monitoring and treatment decisions and improve clinical outcomes.
In some examples, a current diagnostic score may be determined
based on weighted values of the differences between current values
(Z, StO.sub.2, and PTT) of patient 4 and the corresponding baseline
values. For example, processing circuitry 50 may determine a
difference between current values of each of Z, StO.sub.2, and PTT
and the corresponding baseline values of patient 4, as described
with respect to FIG. 6. Then, processing circuitry 50 may determine
a weighted value for each of the differences between the current
values and the corresponding baseline values. Specifically,
processing circuitry 50 determines a weighted value of a difference
between the current Z and the baseline Z of patient 4 (130), a
weighted value of a difference between the current StO.sub.2 and
the baseline StO.sub.2 of patient 4 (132), and a weighted value of
a difference between the current PTT and the baseline PTT of
patient 4 (134).
[0116] In some examples, the weights assigned by processing
circuitry 50 to the difference values may be based on factors such
as a medical history of patient 4. As discussed above with respect
to FIG. 1, processing circuitry 50 of IMD 10 may assign such
weights based on events in the medical history of patient 4, such
as hospital admissions for heart failure, medication changes,
history of systolic heart failure, hypertension, respiratory
illness (e.g., COPD), diabetes, atrial fibrillation, renal failure,
one or more blood disorders (e.g., anemia), one or more sleep
disorders (e.g., sleep apnea), among others. For example, patient 4
may have a medical history of becoming congested, which may
indicate that patient 4 is especially likely to become congested in
the future. Or, population-based data may indicate that patients
having a same or similar profile of baseline values as patient 4
may be particularly likely to become congested (or inadequately
perfused or vasoconstricted). In such a situation, processing
circuitry 50 may assign added weight to the difference between the
current Z and the baseline Z, thereby rendering the diagnostic
score of patient 4 more sensitive to fluctuations in Z values of
patient 4. Similarly, weights assigned by processing circuitry to
the difference values may have negative values, such as if a
medical history of patient 4 or population-based data indicate that
patient 4 is unlikely to become congested (or inadequately perfused
or vasoconstricted). Processing circuitry 50 then may combine the
weighted values of the differences between the current values and
the baseline values, to determine a current diagnostic score for
patient 4 (136), and then compare the current diagnostic score to a
baseline diagnostic score (138). The baseline diagnostic score may
be a diagnostic score previously determined by processing circuitry
50 based on values of one or more evidence levels associated with
the baseline values of patient 4. For example, the baseline
diagnostic score may represent a risk of hospitalization for
patient 4 when patient 4 is compensated, such as when a heart
failure status of patient 4 is stable. Processing circuitry 50 then
may determine an updated heart failure status of patient 4 based on
the comparison of the baseline diagnostic score to the current
diagnostic score (140). As in the method of FIG. 6, processing
circuitry 50 may transmit the updated heart failure status to a
remote computer, such as external device 12. External device 12, or
another remote computer, then may transmit instructions for a
medical intervention (e.g., a change in a drug regimen, or
instructions to schedule a clinician visit or seek medical
attention), to an interface of a user device located with patient
4.
[0117] In some cases, this method of determining a heart failure
status of patient 4 advantageously may provide context to a current
diagnostic score determined for patient 4 by taking into
consideration the extent to which the current diagnostic score
deviates from a baseline diagnostic score. For example, a
relatively greater difference between the baseline diagnostic score
and the current diagnostic score may indicate a more significant
worsening of patient 4's condition than a relatively smaller
difference, even with the current diagnostic score held equal. In
examples where a difference between the baseline and current
diagnostic scores is relatively great (e.g., satisfies a
threshold), external device 12 may transmit instructions for more
aggressive medical interventions to a user device than examples in
which the difference is smaller. In other examples, patient 4 may
be added to a database of particularly at-risk patients, who may be
monitored more closely by a clinician or by one or more of the
devices described herein. In any such examples, treatment may be
further tailored to the specific needs of patient 4 based on the
magnitude of changes in patient 4's heart failure status over
time.
[0118] FIG. 9 is a flow diagram illustrating an example technique
for external device 12 to determine instructions for a medical
intervention based on a heart failure status of patient 4 received
from IMD 10, and transmit the instructions to a user interface. The
method illustrated in FIG. 9 may be used with any of the methods
for determining a heart failure status by IMD 10 described herein,
such as the methods illustrated in FIGS. 6 and 8. In the
illustrated example, external device 12 is configured to receive a
heart failure status of patient 4 from IMD 10, which may be
transmitted to a processing circuitry of external device 12 via
communication circuitry 54 and antenna 26 of IMD 10 (150).
[0119] In some examples, upon receiving the heart failure status of
patient 4 from IMD 10 and prior to determining instructions for a
medical intervention for patient 4, external device 12 may transmit
one or more queries to a user device. For example, external device
12 may ask patient 4 or a caregiver to answer questions about
recent or current activities or symptoms of patient 4, such as
whether patient 4 recently has exercised, taken medications, or
experienced symptoms. In addition, external device 12 may
interrogate IMD 10 for current values of Z, StO.sub.2, and PTT of
patient 4, if IMD 10 did not already transmit the current values to
external device 12. Based on the heart failure status of patient 4,
and optionally based on answers to queries and/or the current
values of patient 4, external device 12 then may determine
instructions for a medical intervention for patient 4 (152).
[0120] External device 12 may determine instructions for multiple
medical interventions for patient 4. For example, external device
12 may determine instructions for each of a congestion status, a
peripheral perfusion status, and a vascular/blood pressure status
of patient 4. For example, based on a congestion status of patient
4, external device 12 may determine instructions for modifying
(e.g., start, stop, increase, or decrease) a dose of a diuretic
drug, taking another type of diuretic drug, and/or modifying a dose
of a venodilator drug (e.g., nitrates). Based on a peripheral
perfusion status of patient 4, external device 12 may determine
instructions for modifying dosages of one or more of a
beta-blocker, ivabradine, or inotrope, or may recommend starting
CRT or changing CRT parameters. Based on a vascular/blood pressure
status of patient 4, external device 12 may determine instructions
for modifying dosages of one or more of a vasoconstrictor agent
(e.g., alpha-agonist) or a vasodilator agent (e.g., alpha-blocker),
or may recommend seeking medical treatment if shock is likely. In
some examples, instructions for medical interventions for patient 4
may take into account the presence of cardiac arrhythmia, as
indicated by ECG signals of patient 4 detected by IMD 10. For
example, instructions determined by external device 12 in the
presence of arrhythmia may include instructions for patient 4 to
avoid taking certain medications, instruct patient 4 to visit a
healthcare facility, or may recommend starting CRT or changing CRT
parameters. Further, in some examples, processing circuitry of IMD
10 may disregard changes in the Z, StO.sub.2, or PTT values that
occur during a cardiac arrhythmia.
[0121] In some examples, external device 12 may determine the
instructions for medical intervention independent of clinician
input, such as by selecting among treatment options stored in a
memory of external device 12 or a centralized database that are
associated with a diagnostic score and the current values of Z,
StO.sub.2, and PTT of patient 4. In other examples, a clinician may
determine the instructions for medical intervention on
substantially the same basis, and input the instructions to
external device 12. External device 12 then may transmit the
instructions to an interface of the user device with patient 4
(154). In some examples, external device 12 may transmit follow-up
queries to patient 4 or a caregiver via the user device after
transmitting the instructions. Such queries may include questions
pertaining to patient 4's understanding of the transmitted
instructions, whether patient 4 has complied with the instructed
medical intervention, and/or whether patient 4 is experiencing
symptoms. External device 12 may store patient 4's responses in a
memory of external device 12, or in a centralized database. A
clinician may review the responses, and remotely follow-up with
patient 4 as needed following any changes to patient 4's heart
failure treatment. In this manner, the techniques and systems
described herein advantageously may enable patient 4 to receive
individualized, frequently updated treatment at less expense than a
comparable number of clinician visits would incur. In addition, the
techniques and systems may help reduce cardiac remodeling that may
be caused by acute decompensation episodes, which in turn may help
minimize the progression of a heart failure condition of patient
4.
[0122] FIGS. 10-12 are flow diagrams illustrating example
techniques for determining appropriate medical interventions for a
patient (e.g., patient 4), depending upon qualitative assessments
of three heart failure parameters corresponding to current values
of Z, StO.sub.2, and PTT for patient 4. The flow diagrams of FIGS.
10-12 are in the form of decision trees that branch off into
specific hemodynamic profiles that may represent a heart failure
status of patient 4 determined IMD 10 according to the methods
described above. In some examples, one or both of external device
12 or a clinician may use the flow diagrams of FIGS. 10-12, in
conjunction with the heart failure status and current Z, StO.sub.2,
and PTT values of patient 4, to determine instructions for a
medical intervention for patient 4. However, for the sake of
clarity, the flow diagrams of FIGS. 10-12 are described below from
the perspective of external device 12, which may include processing
circuitry configured to carry out the decisions illustrated in
FIGS. 10-12.
[0123] FIG. 10 is a flow diagram illustrating an example technique
for determining appropriate medical interventions for a
hypervolemic patient 4 based on trends in the patient 4's tissue
oxygen saturation and pulse transit time. At the top of the flow
chart of FIG. 10, external device 12 has received a heart failure
status of patient 4 from IMD 10 that includes an indication that
patient 4 is hypervolemic (i.e., congested). For example, a current
value of Z transmitted to external device 12 by IMD 10 may be
relatively low, thereby indicating congestion. In some examples,
external device 12 may determine that patient 4 is congested by
comparing the current Z value of patient 4 to a threshold value for
congestion, and determining that the current Z value satisfies the
threshold. Such a threshold value for Z, as well as corresponding
threshold values for StO.sub.2 and PTT described with respect to
FIGS. 10-12, may be stored in a memory of external device 12 or in
a centralized database.
[0124] After determining that patient 4 is congested, external
device 12 may determine a peripheral perfusion status of patient 4
based on a current StO.sub.2 value of patient 4 transmitted to
external device 12 by IMD 10. For example, external device 12 may
compare the current StO.sub.2 value of patient 4 to an StO.sub.2
threshold value indicative of adequate peripheral perfusion, and
determine whether the current StO.sub.2 value is less than,
approximately equal to, or greater than the threshold StO.sub.2
value. External device 12 also may determine a vascular/blood
pressure status of patient 4 by comparing a current PTT value of
patient 4 transmitted to external device 12, by comparing the
current PTT value of patient 4 to a PTT threshold value. The PTT
threshold value may be indicative of a neutral vascular state.
Thus, a current value of PTT that is greater than the PTT threshold
value may indicate vasodilation, a current PTT value that is
approximately equal to the PTT threshold value may indicate neither
vasodilation nor vasoconstriction, and a current PTT value that is
less than the PTT threshold may indicate vasoconstriction.
[0125] By following the decision tree illustrated in FIG. 10 and
comparing the current values of StO.sub.2 and PTT to the
corresponding threshold values, external device 12 may determine a
hemodynamic profile of patient 4 that includes congestion,
peripheral perfusion, and vascular/blood pressure statuses.
However, it should be noted such statuses of patient 4 may not
necessarily reflect absolute values of congestion, tissue
perfusion, or blood pressure of patient 4. For example, a blood
pressure status of patient 4 may not necessarily be a measurement
of an absolute blood pressure value of patient 4, but instead may
indicate a change in blood pressure of patient 4 that may be
associated with a change in afterload. In the example of FIG. 10,
in which example external device 12 initially has determined that
patient 4 is congested, the possible hemodynamic profiles of
patient 4 are shown in the lower-most boxes of the flow chart of
FIG. 10. For example, as shown in the lower-most box of the
left-most branch of FIG. 10, patient 4 has a hemodynamic profile
that indicates that patient 4 is congested ("volume overload"), has
inadequate peripheral perfusion ("depressed CO [cardiac output]"),
and is exhibiting vasodilation ("compensatory vasodilation").
[0126] External device 12 then may use this hemodynamic profile of
patient 4 to determine one or more medical interventions configured
to reduce a likelihood that patient 4 may acutely decompensate,
require hospitalization, or experience other types of adverse
medical events. For example, based on the congested status of
patient 4, external device 12 may instruct patient 4 to undertake
medical interventions configured to decrease excess fluid
retention. Based on the inadequate perfusion of patient 4 in this
example, external device 12 may instruct patient 4 to undertake
medical interventions configured to increase heart rate (if heart
rate is too low), and/or increase contractility (if contractility
is too low). Based on the vasodilation of patient 4 in this
example, external device 12 may instruct patient 4 to undertake
medical interventions configured to cause vasoconstriction and
raise blood pressure. Regardless of the hemodynamic profile of
patient 4 (i.e., the nine lower-most boxes of FIG. 10), external
device 12 may determine one or more medical interventions for
patient 4 based on considerations similar to those described
above.
[0127] In some examples, some of the medical interventions that
external device 12 may recommend based on one status of patient 4
may be conditioned on another status of patient 4. For example,
some medical interventions for inadequate peripheral perfusion may
be conditioned upon a vascular/blood pressure status of patient 4.
Thus, in determining which medical interventions to instruct
patient 4 to undertake, external device 12 may take into account
all three statuses of patient 4 reflected by the hemodynamic
profile. In this manner, the methods and systems described herein
may provide robust heart failure treatment that takes into account
multiple parameters of a heart failure condition of patient 4.
[0128] FIG. 11 is a flow diagram illustrating an example technique
for determining appropriate medical interventions for a hypovolemic
patient 4 based on trends in the patient 4's tissue oxygen
saturation and pulse transit time. The decision tree in FIG. 11 is
substantially similar in function to the decision tree in FIG. 10.
For example, the decision tree in FIG. 11 also provides a method
for external device 12 to determine a hemodynamic profile of
patient 4 based on the congestion, peripheral perfusion, and
vascular/blood pressure statuses of patient 4, and use the
hemodynamic profile in determining which medical interventions to
recommend for patient 4. Unlike the flow diagram of FIG. 10, the
flow diagram of FIG. 11 begins with a determination (e.g., by
external device 12) that patient 4 is hypovolemic (e.g.,
dehydrated). However, as with the decision tree of FIG. 10,
external device 12 may take into account all three statuses of
patient 4 reflected by a hemodynamic profile of FIG. 11 in
determining which medical interventions to instruct patient 4 to
undertake.
[0129] FIG. 12 is a flow diagram illustrating an example technique
for determining appropriate medical interventions for an
optivolemic patient 4 based on trends in the patient 4's tissue
oxygen saturation and pulse transit time. The decision tree in FIG.
12 is substantially similar in function to the decision trees in
FIGS. 10 and 11. For example, the decision tree in FIG. 12 also
provides a method for external device 12 to determine a hemodynamic
profile of patient 4 based on the congestion, peripheral perfusion,
and vascular/blood pressure statuses of patient 4, and use the
hemodynamic profile in determining which medical interventions to
recommend for patient 4. Unlike the flow diagram of FIGS. 10 and
11, the flow diagram of FIG. 12 begins with a determination (e.g.,
by external device 12) that patient 4 is optivolemic (e.g., neither
congested nor dehydrated). However, as with the decision trees of
FIGS. 10 and 11, external device 12 may take into account all three
statuses of patient 4 reflected by a hemodynamic profile of FIG. 12
in determining which medical interventions to instruct patient 4 to
undertake.
[0130] Although processing circuitry 50 of IMD 10 and processing
circuitry of external device 12 is described above as being
configured to perform one or more of the steps of the techniques
illustrated in FIGS. 6-12, any steps of the techniques described
herein may be performed by processing circuitry of the other of IMD
10 or external device 12, or by one or more other devices. For
example, processing circuitry of external device 12, or of any
other suitable implantable or external device or server, may be
configured to perform one or more of the steps described as being
performed by processing circuitry 50 of IMD 10. In other examples,
processing circuitry 50 of IMD 10, or of any other suitable
implantable or external device or server, may be configured to
perform one or more of the steps described as being performed by
processing circuitry of external device 12. Such other implantable
or external devices may include, for example, an implantable
pacemaker or ICD, an external monitoring device, or any other
suitable device. In addition, although the optical sensors and
electrodes are described herein as being positioned on a housing of
IMD 10, in other examples, such optical sensors and/or electrodes
may be positioned on a housing of another device implanted in or
external to patient 4, such as a transvenous, subcutaneous, or
extravascular pacemaker or ICD, or coupled to such a device by one
or more leads.
[0131] In some examples, the techniques described herein (e.g.,
with respect to FIGS. 6-12) may include determining values of one
or more other parameters in addition to or instead of any of Z,
StO.sub.2, and PTT. As described above with respect to FIG. 1,
sensors on IMD 10 or one or more other implanted or external
devices may be configured to sense signals associated with such
parameters. For example, one or more implanted or external devices
of medical system 2 (e.g., IMD 10) may include one or more sensors
configured to sense blood or tissue levels of one or more compounds
associated with kidney function of patient 4, such as creatinine or
blood urea nitrogen. In such examples, techniques for determining a
heart failure status of patient 4 may include determining, by
processing circuitry of IMD 10, external device 12, or one or more
other implanted or external devices or servers, a current value of
the one or more other parameters, comparing such a current value to
a corresponding baseline, and using the comparison in determining
the heart failure status of patient 4. In some examples, such one
or more other parameters may not be directly associated with
changes in a heart failure status, but may provide other
information about the health of patient 4, such as activity levels
or sleep patterns. In any such examples, external device 12, or
another suitable device, may determine the instructions for medical
intervention for patient 4 at least partially based on a status of
patient 4 associated with the one or more other parameters, such as
a kidney status of patient 4 associated with a current creatinine
value of patient 4.
[0132] Various aspects of the techniques may be implemented within
one or more processors, including one or more microprocessors,
DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete
logic circuitry, as well as any combinations of such components,
embodied in programmers, such as physician or patient programmers,
electrical stimulators, or other devices. The term "processor" or
"processing circuitry" may generally refer to any of the foregoing
logic circuitry, alone or in combination with other logic circuitry
or any other equivalent circuitry.
[0133] In one or more examples, the functions described in this
disclosure may be implemented in hardware, software, firmware, or
any combination thereof. If implemented in software, the functions
may be stored on, as one or more instructions or code, a
computer-readable medium and executed by a hardware-based
processing unit. Computer-readable media may include
computer-readable storage media forming a tangible, non-transitory
medium. Instructions may be executed by one or more processors,
such as one or more DSPs, ASICs, FPGAs, general purpose
microprocessors, or other equivalent integrated or discrete logic
circuitry. Accordingly, the terms "processor" or "processing
circuitry" as used herein may refer to one or more of any of the
foregoing structures or any other structure suitable for
implementation of the techniques described herein.
[0134] In addition, in some aspects, the functionality described
herein may be provided within dedicated hardware and/or software
modules. Depiction of different features as modules or units is
intended to highlight different functional aspects and does not
necessarily imply that such modules or units must be realized by
separate hardware or software components. Rather, functionality
associated with one or more modules or units may be performed by
separate hardware or software components, or integrated within
common or separate hardware or software components. Also, the
techniques could be fully implemented in one or more circuits or
logic elements. The techniques of this disclosure may be
implemented in a wide variety of devices or apparatuses, including
an IMD, an external programmer, a combination of an IMD and
external programmer, an integrated circuit (IC) or a set of ICs,
and/or discrete electrical circuitry, residing in an IMD and/or
external programmer.
[0135] Various aspects of the disclosure have been described. These
and other aspects are within the scope of the following claims.
* * * * *