System and method for evaluating a patient status for use in heart failure assessment

• US 20070293738A1
• Filed: 08/20/2007
• Published: 12/20/2007
• Est. Priority Date: 06/03/1999
• Status: Active Grant

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Bardy, Gust
• Granted Patent: US 9,526,456 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• 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 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0215 by means inserted into the body catheters A61M25/00
• CPC Class Codes: A61B 5/0826 Detecting or evaluating apnoea events A61B5/4818 takes precedence
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/333 Recording apparatus specially adapted therefor
• CPC Class Codes: A61B 5/4878 Evaluating oedema
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• 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 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 7/02 Stethoscopes acoustic details thereof G10K11/00
• CPC Class Codes: A61N 1/37258 Alerting the patient
• CPC Class Codes: A61N 1/37282 : characterised by communication with experts in remote locations using a network
• CPC Class Codes: A61N 1/39622 : Pacing therapy
• CPC Class Codes: G16H 10/60 : for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 : ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/67 : for remote operation
• CPC Class Codes: G16H 50/00 : ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: Y10S 128/92 : Computer assisted medical diagnostics

Abstract

A system and method for evaluating a patient status from sampled physiometry for use in heart failure assessment is presented. Physiological measures, including at least one of direct measures regularly recorded on a substantially continuous basis by a medical device and measures derived from the direct measures are stored. At least one of those of the physiological measures, which relate to a same type of physiometry, and those of the physiological measures, which relate to a different type of physiometry are sampled. A status is determined for a patient through analysis of those sampled measures assembled from a plurality of recordation points. The sampled measures are evaluated. Trends that are indicated by the patient status, including one of a status quo and a change, which might affect cardiac performance of the patient, are identified. Each trend is compared to worsening heart failure indications to generate a notification of parameter violations.

Claims

1. A system for evaluating a patient status for use in heart failure assessment, comprising:

a data module to assemble physiological measures, which were directly recorded as data on a substantially continuous basis by a medical device for a patient or indirectly derived from the data;

a status module to determine a status for the patient through sampling and analysis of the physiological measures over a plurality of data assembly points; and

an evaluation module to evaluating the physiological measures relative to the patient status, comprising;

an analysis module to analyze any trend comprising one of a status quo and a change in cardiac performance; and

a comparison module to compare the trend to worsening heart failure indications.

2. A system according to claim 1, further comprising:

a quality of life module to associate quality of life measures chronicled by the patient with the physiological measures.

3. A system according to claim 1, wherein the change in cardiac performance is selected from the group comprising an onset, progression, and regression of a cardiac performance parameter.

4. A system according to claim 1, further comprising:

a sampling module to form sampling sets, comprising at least one of;

a peer module to group a plurality of the physiological measures, which each relate to a same type of physiometry, into one or more peer measures sets; and

a sibling module to group a plurality of the physiological measures, which each relate to a different type of physiometry, into one or more sibling measures sets,

wherein one or more of the sampling sets is selected as the physiological measures.

5. A system according to claim 1, wherein physiological measures from one or more of the physiological measures for the patient, physiological measures for a peer group, and physiological measures for an overall patient population.

6. A system according to claim 1, further comprising:

a feedback module to provide tiered feedback from the patient status, comprising at least one of;

a first level module to communicate, at a first level, an interpretation of the patient status;

a second level module to communicate, at a second level, a notification of potential medical concern based on the patient status;

a third level module to communicate, at a third level, a notification of potential medical concern based on the patient status to medical personnel; and

a fourth level module to communicate, at a fourth level, a set of reprogramming instructions based on the patient status to a medical device.

7. A system according to claim 1, wherein the worsening heart failure indications are selected from the group comprising pulmonary artery pressure, left atrial pressure, dyspnea, orthopnea, pulmonary edema, peripheral edema, and fatigue.

8. A system according to claim 1, further comprising:

a measurement module to measure one or more of pulmonary artery pressure, heart rate, heart sounds, intrathoracic impedance, respiration, posture, lung fluid, activity, weight, and physiological response to activity.

9. A system according to claim 1, further comprising:

a reprogramming module to reprogram a medical device based on evaluation of the physiological measures.

10. A system according to claim 9, wherein the worsening heart failure indications are factored into the reprogramming.

11. A system according to claim 1, wherein respiration rate is tracked through the medical device, further comprising:

a notification module to generate a notification triggered by a parameter assigned to the respiration rate.

12. A system according to claim 11, wherein the parameter comprises one or more of an upper limit parameter applied over a short term and a counter parameter applied over a long term.

13. A system according to claim 1, wherein the medical device comprises one of an implantable medical device and an external medical device.

14. A method for evaluating a patient status for use in heart failure assessment, comprising:

assembling physiological measures, which were directly recorded as data on a substantially continuous basis by a medical device for a patient or indirectly derived from the data;

determining a status for the patient through sampling and analysis of the physiological measures over a plurality of data assembly points; and

evaluating the physiological measures relative to the patient status by analyzing any trend comprising one of a status quo and a change in cardiac performance and comparing the trend to cardiac decompensation indications.

15. A method according to claim 14, further comprising:

associating quality of life measures chronicled by the patient with the physiological measures.

16. A method according to claim 14, wherein the change in cardiac performance is selected from the group comprising an onset, progression, and regression of a cardiac performance parameter.

17. A method according to claim 14, further comprising:

forming sampling sets, comprising at least one of;

grouping a plurality of the physiological measures, which each relate to a same type of physiometry, into one or more peer measures sets; and

grouping a plurality of the physiological measures, which each relate to a different type of physiometry, into one or more sibling measures sets; and

selecting one or more of the sampling sets as the physiological measures.

18. A method according to claim 14, further comprising:

including physiological measures from one or more of the physiological measures for the patient, physiological measures for a peer group, and physiological measures for an overall patient population.

19. A method according to claim 14, further comprising:

providing tiered feedback from the patient status, comprising at least one of;

at a first level, communicating an interpretation of the patient status;

at a second level, communicating a notification of potential medical concern based on the patient status;

at a third level, communicating a notification of potential medical concern based on the patient status to medical personnel; and

at a fourth level, communicating a set of reprogramming instructions based on the patient status to a medical device.

20. A method according to claim 14, wherein the worsening heart failure indications are selected from the group comprising pulmonary artery pressure, left atrial pressure, dyspnea, orthopnea, pulmonary edema, peripheral edema, and fatigue.

21. A method according to claim 14, further comprising:

measuring one or more of pulmonary artery pressure, heart rate, heart sounds, intrathoracic impedance, respiration, posture, lung fluid, activity, weight, and physiological response to activity.

22. A method according to claim 14, further comprising:

reprogramming a medical device based on evaluation of the physiological measures.

23. A method according to claim 22, further comprising:

factoring the worsening heart failure indications into the reprogramming.

24. A method according to claim 14, further comprising:

tracking respiration rate through the medical device; and

generating a notification triggered by a parameter assigned to the respiration rate.

25. A method according to claim 24, wherein the parameter comprises one or more of an upper limit parameter applied over a short term and a counter parameter applied over a long term.

26. A method according to claim 14, wherein the medical device comprises one of an implantable medical device and an external medical device.

27. A system for evaluating a patient status from sampled physiometry for use in heart failure assessment, comprising:

a storage module to store physiological measures comprising at least one of direct measures regularly recorded on a substantially continuous basis by a medical device for a patient and measures derived from the direct measures;

a sampling module to sample at least one of those of the physiological measures, which each relate to a same type of physiometry, and those of the physiological measures, which each relate to a different type of physiometry;

a status module to determine a status for the patient through analysis of those sampled physiological measures assembled from a plurality of recordation points; and

an evaluation module to evaluate the sampled physiological measures, comprising;

an analysis module to identify any trends that are indicated by the patient status comprising one of a status quo and a change, which might affect cardiac performance of the patient; and

a comparison module to compare each such trend to cardiac decompensation indications to generate a notification of parameter violations.

28. A system according to claim 27, further comprising:

a reprogramming module to reprogram a medical device based on extended evaluation of the direct measures and the derived measures.

29. A system according to claim 27, further comprising:

a tracking module to track respiration rate of the patient on a regular basis through the medical device; and

a notification module to generate a notification triggered by one or more of an upper limit parameter applied over a short term and a counter parameter applied over a long term.

30. A method for evaluating a patient status from sampled physiometry for use in heart failure assessment, comprising:

storing physiological measures comprising at least one of direct measures regularly recorded on a substantially continuous basis by a medical device for a patient and measures derived from the direct measures;

sampling at least one of those of the physiological measures, which each relate to a same type of physiometry, and those of the physiological measures, which each relate to a different type of physiometry;

determining a status for the patient through analysis of those sampled physiological measures assembled from a plurality of recordation points; and

evaluating the sampled physiological measures, comprising;

identifying any trends that are indicated by the patient status comprising one of a status quo and a change, which might affect cardiac performance of the patient; and

comparing each such trend to cardiac decompensation indications to generate a notification of parameter violations.

31. A method according to claim 30, further comprising:

reprogramming a medical device based on extended evaluation of the direct measures and the derived measures.

32. A method according to claim 30, further comprising:

tracking respiration rate of the patient on a regular basis through the medical device; and

generating a notification triggered by one or more of an upper limit parameter applied over a short term and a counter parameter applied over a long term.