Methods and apparatus for stratifying risk of heart failure decompensation

• US 10,143,385 B2
• Filed: 05/20/2014
• Issued: 12/04/2018
• Est. Priority Date: 05/20/2013
• Status: Active Grant

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Sweeney, Robert J., Zhang, Yi, An, Qi, Thakur, Pramodsingh Hirasingh
• Primary Examiner(s): Natnithithadha, Navin
• Assistant Examiner(s): Shostak, Andrey
• Application Number:
  US14/282,353
• Publication Number:
  US 20140343439A1
• Time in Patent Office: 1,659 Days
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0826 Detecting or evaluating apnoea events A61B5/4818 takes precedence
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/201 Assessing renal or kidney functions
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Devices and methods for identifying patient at elevated risk of developing future heart failure (HF) events, such as events indicative of HF decompensation status, are described. The devices and methods can stratify the risk using sensor signals or signal metrics selected in accordance with patient chronic conditions. A medical device can receive a patient status input including at least a first and a second chronic condition indicators, sense one or more physiologic signals from the patient, and generate a plurality of signal metrics from the physiologic signals when the first chronic condition indicator and the second chronic condition indicator meets respective criterion. One or more patient-specific signal metrics can be selected from a group including the signal metrics selected for both the first and the second chronic conditions. A risk stratification algorithm can use the selected one or more patient-specific signal metrics to compute a composite risk index indicative of the probability of the patient later developing an event indicative of worsening of HF.

Claims

1. A medical device, comprising:

a signal analyzer circuit, including;

a patient status input unit configured to receive at least a first demographic characteristic indicator and a second demographic characteristic indicator of a patient, the second demographic characteristic indicator non-identical to the first demographic characteristic indicator;

a signal receiver circuit configured to receive one or more physiologic signals of the patient;

a signal metrics generator circuit configured to generate a plurality of signal metrics from the one or more physiologic signals, including to generate a first set of one or more signal metrics in response to the first demographic characteristic indicator meeting at least one first specified criterion, and to generate a second set of signal metrics in response to the second demographic characteristic indicator meeting at least one second specified criterion; and

a patient-specific signal metric selector circuit configured to select a subset of patient-specific signal metrics from the first and second sets of signal metrics using signal metric performance measures of at least one metric from the first and second sets of signal metrics; and

a risk stratification circuit configured to generate a composite risk index using the selected subset of patient-specific signal metrics, the composite risk index indicative of the probability of the patient later developing an event indicative of worsening of heart failure, the risk stratification circuit comprising a risk report generator configured to generate a report to inform a user of an elevated risk of the patient developing the event indicative of worsening of heart failure.

2. The device of claim 1, wherein the risk stratification circuit is configured to generate a composite risk index indicative of the probability of the patient developing a heart failure decompensation event within a specified timeframe.

3. The device of claim 1, wherein the patient status input unit is configured to receive a first chronic disease indicator and a second chronic disease indicator of the patient, wherein the signal metrics generator circuit is configured to generate the first set of signal metrics further based on the first chronic disease indicator, and to generate the second set of signal metrics further based on the second chronic disease indicator.

4. The device of claim 1, wherein:

the signal receiver circuit is configured to be coupled to at least one physiologic sensor configured to sense the one or more physiologic signals from the patient;

the signal metrics generator circuit comprises a signal metrics performance analyzer circuit configured to generate, for the first and second sets of signal metrics, respective signal metrics performance measures selected from the group consisting of a signal quality measure, a signal sensitivity measure, and a signal specificity measure; and

the patient-specific signal metrics selector circuit is configured to select the subset of patient-specific signal metrics based on the respective signal metric performance measures.

5. The device of claim 4, wherein the signal metrics performance analyzer circuit is configured to generate a sensitivity of a daily maximum respiration rate (MRR) indicative of a relative change from a baseline daily MRR, and wherein the signal metrics generator circuit is configured to generate a set of signal metrics including the daily MRR when the patient has no prior renal disease.

6. The device of claim 1, wherein the risk stratification circuit is configured to generate for each metric in the subset of patient-specific signal metrics respective risk scores using the first or second demographic characteristic indicators, and to calculate the composite risk index using the respective risk scores.

7. The device of claim 6, wherein the risk stratification circuit is configured to calculate the composite risk index using a weighted function of the risk scores for the subset of patient-specific signal metrics.

8. The device of claim 1, wherein the risk stratification circuit is configured to generate two or more categorical risk levels using a comparison between the composite risk index and a reference measure, the two or more categorical risk levels indicative of elevated risk of the patient later developing the event indicative of worsening of heart failure.

9. The device of claim 8, wherein the reference measure is computed using signal metrics of a patient population, at least a portion of the patient population having the first and the second demographic characteristic indicators.

19. The system of claim 1, wherein the patient-specific signal metric selector circuit is configured to select the patient-specific signal metric subset including at least one signal metric from an intersection of the first and second sets of signal metrics.

20. The system of claim 1, wherein the patient-specific signal metric selector circuit is configured to select the patient-specific signal metric subset including at least one signal metric from the first set of signal metrics and at least one signal metric from the second set of signal metrics.

10. A method of operating a medical device to determine a patient risk of worsening of heart failure, comprising:

receiving at least a first demographic characteristic indicator and a second demographic characteristic indicator of a patient via a patient status input unit included in a signal analyzer circuit, the second demographic characteristic indicator non-identical to the first demographic characteristic indicator;

receiving one or more physiologic signals of the patient via a signal receiver circuit;

generating a plurality of signal metrics from the one or more physiologic signals via a signal metrics generator circuit, including generating a first set of one or more signal metrics in response to the first demographic characteristic indicator meeting at least one first specified criterion, and generating a second set of signal metrics in response to the second demographic characteristic indicator meeting at least one second specified criterion;

selecting, via a patient-specific signal metric selector circuit, a subset of patient-specific signal metrics from the first and second sets of signal metrics based on signal metrics performance measures of at least one metric from the first and second sets of signal metrics;

generating, via a risk stratification circuit, a composite risk index using the selected subset of patient-specific signal metrics, the composite risk index indicative of the probability of the patient later developing an event indicative of worsening of heart failure; and

generating, via a risk report generator, a report to inform a user of an elevated risk of the patient developing the event indicative of worsening of heart failure.

11. The method of claim 10, wherein generating a composite risk index includes generating an indicator of probability of the patient developing a heart failure decompensation event within a specified timeframe.

12. The method of claim 10, further comprising receiving a first chronic disease indicator and a second chronic disease indicator of the patient, generating the first set of signal metrics further based on the first chronic disease indicator, and generating the second set of signal metrics further based on the second chronic disease indicator.

13. The method of claim 10, comprising

generating, for the first and second sets of signal metrics, respective signal metrics performance measures selected from the group consisting of a signal quality measure, a signal sensitivity measure, and a signal specificity measure;

and

wherein selecting the subset of patient-specific signal metrics is based on the respective signal metric performance measures.

14. The method of claim 13, wherein generating the signal sensitivity measure includes calculating a relative change of the respective signal metric from a first state to a second state, the second state including temporal information non-identical to that of the first state.

15. The method of claim 10, wherein generating a composite risk index includes generating, for each metric in the selected subset of patient-specific signal metrics, respective risk scores using at least the first and the second demographic characteristic indicators, and calculating the composite risk index using the respective risk scores.

16. The method of claim 15, wherein calculating the composite risk index includes generating, for each metric in the selected subset of patient-specific signal metrics respective weight factors, and calculating the composite risk index using a combination of the respective risk scores respectively weighted by the weight factors.

17. The method of claim 16, wherein the weight factors for each metric in the selected subset of patient-specific signal metrics are determined using respective signal metrics performance measures.

18. The method of claim 10, further comprising categorizing the event indicative of worsening of heart failure into one of two or more categorical risk levels using a comparison between the composite risk index and a reference measure, the reference measure computed using signal metrics of a patient population having the first and the second demographic characteristics.