System and method for providing diagnosis and monitoring of myocardial ischemia for use in automated patient care

• US 6,827,690 B2
• Filed: 04/04/2002
• Issued: 12/07/2004
• Est. Priority Date: 11/16/1999
• Status: Expired due to Term

• Current Assignee: Cardiac Intelligence Corp (Boston Scientific Corporation)
• Original Assignee: Cardiac Intelligence Corp (Boston Scientific Corporation)
• Inventors: Bardy, Gust H.
• Primary Examiner(s): EVANISKO, GEORGE ROBERT
• Application Number:
  US10/116,654
• Publication Number:
  US 20020143262A1
• Time in Patent Office: 978 Days
• Field of Search: 600/300, 600/301, 600/508, 600/509, 600/513, 600/518, 128/920, 128/923, 607/4, 607/5, 607/9, 607/14
• US Class Current: 600/508
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/02 Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
• 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 5/0215 by means inserted into the body catheters A61M25/00
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/029 Measuring or recording blood output from the heart, e.g. minute volume A61B8/065 takes precedence
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61N 1/36507 controlled by gradient or slope of the heart potential
• 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 20/40 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

Abstract

A system and method for providing diagnosis and monitoring of myocardial ischemia for use in automated patient care is described. At least one recorded physiological measure is compared to at least one other recorded physiological measure on a substantially regular basis to quantify a change in patient pathophysiological status for equivalent patient information. An absence, an onset, a progression, a regression, and a status quo of myocardial ischemia is evaluated dependent upon the change in patient pathophysiological status.

Claims

1. A system for providing diagnosis and monitoring of myocardial ischemia for use in automated patient care, comprising:

an implantable medical device recording at least one physiological measure and at least one other physiological measure on a substantially continuous basis;

a database storing monitoring sets comprising the at least one recorded physiological measure and the at least one other recorded physiological measure;

a comparison module comparing the at least one recorded physiological measure to the at least one other recorded physiological measure on a substantially regular basis to quantify a change in patient pathophysiological status for corresponding patient information;

a diagnostic module comparing the change in patient pathophysiological status to an indicated threshold corresponding to a quantifiable physiological measure indicative of myocardial ischemia; and

an analysis module evaluating an onset, a progression, a regression, and a status quo of myocardial ischemia dependent upon the comparison of the patient pathophysiological status to the indicator threshold.

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

a database module retrieving the at least one recorded physiological measure and the at least one other recorded physiological measure from at least one of the monitoring sets stored in the database.

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

a server system collecting the at least one recorded physiological measure and the at least one other recorded physiological measure into each monitoring set recorded on a substantially continuous basis or derived therefrom.

4. A system according to claim 3, further comprising:

an external medical device recording the at least one recorded physiological measure and the at least one other recorded physiological measure.

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

the analysis module evaluating an absence, an onset, a progression, a regression, and a status quo of diseases other than myocardial ischemia dependent upon the change in patient pathophysiological status.

6. A system according to claim 1, wherein the monitoring sets further comprise at least one quality of life measure and at least one other quality of life measure, further comprising:

a diagnostic module comparing the at least one recorded quality of life measure to the at least one other recorded quality of life measure on a substantially regular basis to qualify a change in patient pathophysiological status.

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

a stickiness indicator defined for the at least one physiological measure corresponding to a temporal boundary on one of patient diagnosis and treatment;

a diagnostic module timing each change in patient pathophysiological status for corresponding patient information and determining one of a revised patient diagnosis and treatment responsive to each change in patient pathophysiological status with a timing exceeding the stickiness indicator.

8. A system according to claim 1, wherein the monitoring sets further comprise a reference baseline, further comprising:

a diagnostic module comparing the change in patient pathophysiological status to the reference baseline comprising recorded physiological measures recorded during an initial time period.

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

a diagnostic module comparing the change in patient pathophysiological status to patient information corresponding to at least one of an individual patient, a peer group, and a overall patient population.

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

a diagnostic module grading the change in patient pathophysiological status on a fixed scale based on a degree of deviation from a pre-defined indicator threshold and performing a summation over a plurality of the graded changes to determine an overall change in patient pathophysiological status.

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

a diagnostic module determining probabilistic weightings of the change in patient pathophysiological status on a statistical deviation and trends via linear fits from a pre-defined indicator threshold and performing a summation over a plurality of the probabilistic weightings to determine an overall change in patient pathophysiological status.

12. A method for providing diagnosis and monitoring of myocardial ischemia for use in automated patient care, comprising:

recording at least one physiological measure and at least one other physiological measure on a substantially continuous basis with an implantable medical device;

storing monitoring sets comprising the at least one recorded physiological measure and the at least one other recorded physiological measure;

comparing the at least one recorded physiological measure to the at least one other recorded physiological measure on a substantially regular basis to quantify a change in patient pathophysiological status for corresponding patient information;

comparing the change in patient pathophysiological status to an indicator threshold corresponding to a quantifiable physiological measure indicative of myocardial ischemia; and

evaluating an onset, a progression, a regression, and a status quo of myocardial ischemia dependent upon the comparison of the patient pathophysiological status to the indicator threshold.

13. A method according to claim 12, further comprising:

retrieving the at least one recorded physiological measure and the at least one other recorded physiological measure from at least one of the monitoring sets stored in the database.

14. A method according to claim 13, further comprising:

collecting the at least one recorded physiological measure and the at least one other recorded physiological measure into each monitoring set recorded on a substantially continuous basis or derived therefrom.

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

recording the at least one recorded physiological measure and the at least one other recorded physiological measure with an external medical device.

16. A method according to claim 12, further comprising:

evaluating an absence, an onset, a progression, a regression, and a status quo of diseases other than myocardial ischemia dependent upon the change in patient pathophysiological status.

17. A method according to claim 12, wherein the monitoring sets further comprise at least one quality of life measure and at least one other quality of life measure, further comprising:

comparing the at least one recorded quality of life measure to the at least one other recorded quality of life measure on a substantially regular basis to qualify a change in patient pathophysiological status.

18. A method according to claim 12, further comprising:

defining a stickiness indicator for the at least one physiological measure corresponding to a temporal boundary on one of patient diagnosis and treatment;

timing each change in patient pathophysiological status for corresponding patient information; and

determining one of a revised patient diagnosis and treatment responsive to each change in patient pathophysiological status with a timing exceeding the stickiness indicator.

19. A method according to claim 12, wherein the monitoring sets further comprise a reference baseline, further comprising:

comparing the change in patient pathophysiological status to the reference baseline comprising recorded physiological measures recorded during an initial time period.

20. A method according to claim 12, further comprising:

comparing the change in patient pathophysiological status to patient information corresponding to at least one of an individual patient, a peer group, and a overall patient population.

21. A method according to claim 12, further comprising:

grading the change in patient pathophysiological status on a fixed scale based on a degree of deviation from a pre-defined indicator threshold; and

performing a summation over a plurality of the graded changes to determine an overall change in patient pathophysiological status.

22. A method according to claim 12, further comprising:

determining probabilistic weightings of the change in patient pathophysiological status on a statistical deviation and trends via linear fits from a pre-defined indicator threshold; and

performing a summation over a plurality of the probabilistic weightings to determine an overall change in patient pathophysiological status.

23. A computer-readable storage medium for a device holding code for performing the method according to claim 12.