System and method for managing respiratory insufficiency in conjunction with heart failure assessment

• US 20070293779A1
• Filed: 08/20/2007
• Published: 12/20/2007
• Est. Priority Date: 11/16/1999
• 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 8,231,540 B2
• Time in Patent Office: Days
• US Class Current: 600/529
• CPC Class Codes: A61B 2505/03 Intensive care
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/0215 by means inserted into the body catheters A61M25/00
• 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 5/0535 Impedance plethysmography for measuring blood flow A61B5/0295
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• 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 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14539 for measuring pH
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61N 1/3624 occurring in the atrium, i.e. atrial tachycardia
• 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 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 : for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 70/60 : relating to pathologies
• CPC Class Codes: Y10S 128/92 : Computer assisted medical diagnostics
• CPC Class Codes: Y10S 128/923 : by comparison of patient data to other data

Abstract

A system and method for evaluating a patient status from sampled physiometry for use in respiratory insufficiency management and heart failure assessment is presented. Physiological measures are stored and include direct measures regularly recorded on a substantially continuous basis by a medical device for a patient or measures derived from the direct measures. The physiological measures are sampled, 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 is determined through analysis of those sampled physiological measures assembled from a plurality of recordation points. The sampled physiological measures are evaluated. Any trends are identified and include one of a status quo and a change, which might affect cardiac performance or respiratory performance. Each such trend is compared to applicable indications of worsening heart failure and respiratory insufficiency to generate a notification of parameter violations.

Claims

1. A system for managing respiratory insufficiency in conjunction with 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 evaluate 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 at least one of cardiac performance and respiratory performance; and

a comparison module to compare the trend to applicable indications of worsening heart failure and respiratory insufficiency.

2. A system according to claim 1, wherein the trend relates to at least one of a finding of reduced exercise capacity and respiratory distress.

3. A system according to claim 2, wherein the finding of reduced exercise capacity is selected from the group comprising decreased cardiac output, decreased mixed venous oxygen score, decreased patient activity score and decreased exercise tolerance.

4. A system according to claim 2, wherein the finding of respiratory distress is selected from the group comprising a spike in patient activity score, a spike in pulmonary artery pressure, a spike in right ventricular pressure, a spike in transthoracic impedance, increased respiratory rate, increased minute ventilation, increased temperature, decreased QT interval, decreased arterial oxygen and decreased arterial carbon dioxide.

5. 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.

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

an indicator module to define stickiness indicators comprising a temporal bound on change of one or more of the physiological measures;

an evaluation module to evaluate a time span occurring between a plurality of the data assembly points, which are distinct; and

a revision module to revise patient treatment in a manner corresponding to a rate of the change over the time span.

7. A system according to claim 1, wherein the change in at least one of cardiac performance and respiratory performance is selected from the group comprising an onset, progression, and regression of either a cardiac performance or a respiratory performance parameter.

8. 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.

9. 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.

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

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

11. A system according to claim 10, wherein either the worsening heart failure indications or the respiratory insufficiency are factored into the reprogramming.

12. 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.

13. A system according to claim 12, 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.

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

15. A method for managing respiratory insufficiency in conjunction with 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 at least one of cardiac performance and respiratory performance and comparing the trend to applicable indications of worsening heart failure and respiratory insufficiency.

16. A method according to claim 15, wherein the trend relates to at least one of a finding of reduced exercise capacity and respiratory distress.

17. A method according to claim 16, wherein the finding of reduced exercise capacity is selected from the group comprising decreased cardiac output, decreased mixed venous oxygen score, decreased patient activity score and decreased exercise tolerance.

18. A method according to claim 16, wherein the finding of respiratory distress is selected from the group comprising a spike in patient activity score, a spike in pulmonary artery pressure, a spike in right ventricular pressure, a spike in transthoracic impedance, increased respiratory rate, increased minute ventilation, increased temperature, decreased QT interval, decreased arterial oxygen and decreased arterial carbon dioxide.

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

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

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

defining stickiness indicators comprising a temporal bound on change of one or more of the physiological measures;

evaluating a time span occurring between a plurality of the data assembly points, which are distinct; and

revising patient treatment in a manner corresponding to a rate of the change over the time span.

21. A method according to claim 15, wherein the change in at least one of cardiac performance and respiratory performance is selected from the group comprising an onset, progression, and regression of either a cardiac performance or a respiratory performance parameter.

22. A method according to claim 15, 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.

23. A method according to claim 15, 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.

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

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

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

factoring either the worsening heart failure indications or the respiratory insufficiency into the reprogramming.

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

tracking respiration rate through the medical device; and

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

27. A method according to claim 26, 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.

28. A method according to claim 15, wherein the medical device comprises one of an implantable medical device and an external medical device.

29. A system for evaluating a patient status from sampled physiometry for use in respiratory insufficiency management and 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 one or more of cardiac performance and respiratory performance of the patient; and

a comparison module to compare each such trend to applicable indications of worsening heart failure and respiratory insufficiency to generate a notification of parameter violations.

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

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

31. A system according to claim 29, 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.

32. A method for evaluating a patient status from sampled physiometry for use in respiratory insufficiency management and 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 one or more of cardiac performance and respiratory performance of the patient; and

comparing each such trend to applicable indications of worsening heart failure and respiratory insufficiency to generate a notification of parameter violations.

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

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

34. A method according to claim 32, 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.