System And Method For Automated Diagnosis Of Myocardial Ischemia Through Remote Monitoring

• US 20080058661A1
• Filed: 10/31/2007
• Published: 03/06/2008
• 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 8,672,856 B2
• Time in Patent Office: Days
• US Class Current: 600/513
• 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 automated diagnosis of myocardial ischemia through remote monitoring is described. Physiological measures comprising data either recorded on a regular basis by a medical device or derived therefrom is stored. Qualitative measures associated with the physiological measures are matched. Indications of myocardial ischemia are remotely identified. The qualitative measures for both of a reduction in exercise capacity and respiratory distress occurring contemporaneously are examined. The qualitative measures for angina that accompanies the reduction in exercise capacity and the respiratory distress are evaluated. A time course for each of the indications is determined. A patient status is formed comprising an onset of myocardial ischemia conditioned on the time course comprising a short duration.

Claims

1. A system for automated diagnosis of myocardial ischemia through remote monitoring, comprising:

a database module storing physiological measures comprising data either recorded on a regular basis by a medical device or derived therefrom;

a comparison module matching qualitative measures associated with the physiological measures;

an analysis module remotely identifying indications of myocardial ischemia, by examining the qualitative measures for both of a reduction in exercise capacity and respiratory distress occurring contemporaneously, and evaluating the qualitative measures for angina that accompanies the reduction in exercise capacity and the respiratory distress; and

a diagnostic module determining a time course for each of the indications, and forming a patient status comprising an onset of myocardial ischemia conditioned on the time course comprising a short duration.

2. A system according to claim 1, wherein the analysis module further compares each of the physiological measures against an indicator threshold comprising one of a finite cutoff value, weighted value, and statistical range, and further evaluates a potential onset, progression, regression, and status quo of myocardial ischemia based on findings of the indicator threshold comparisons.

3. A system according to claim 2, wherein the analysis module further assigns the weighted value comprising a highest weight to wall motion abnormalities in the reduction in exercise capacity and respiratory distress examinations.

4. A method for automated diagnosis of myocardial ischemia through remote monitoring, comprising:

storing physiological measures comprising data either recorded on a regular basis by a medical device or derived therefrom;

matching qualitative measures associated with the physiological measures;

remotely identifying indications of myocardial ischemia, comprising;

examining the qualitative measures for both of a reduction in exercise capacity and respiratory distress occurring contemporaneously; and

evaluating the qualitative measures for angina that accompanies the reduction in exercise capacity and the respiratory distress;

determining a time course for each of the indications; and

forming a patient status comprising an onset of myocardial ischemia conditioned on the time course comprising a short duration.

5. A method according to claim 4, further comprising:

comparing each of the physiological measures against an indicator threshold comprising one of a finite cutoff value, weighted value, and statistical range; and

evaluating a potential onset, progression, regression, and status quo of myocardial ischemia based on findings of the indicator threshold comparisons.

6. A method according to claim 5, further comprising:

assigning the weighted value comprising a highest weight to wall motion abnormalities in the reduction in exercise capacity and respiratory distress examinations.

7. A system for automated diagnosis of myocardial ischemia through remote monitoring, comprising:

a database module storing physiological measures comprising data either recorded on a regular bases by a medical device or derived therefrom;

a comparison module matching qualitative measures associated with the physiological measures;

an analysis module remotely identifying indications of myocardial ischemia, by examining the qualitative measures for angina, and further evaluating the qualitative measures for one of a reduction in exercise capacity and of respiratory distress, which accompanies the angina; and

a diagnostic module determining a time course for each of the indications, and forming a patient status comprising an onset of myocardial ischemia conditioned on the time course comprising a short duration.

8. A system according to claim 7, wherein the analysis module further compares each of the physiological measure against an indicator threshold comprising one of a finite cutoff value, weighted value, and statistical range, and further evaluates a potential onset, progression, regression, and status quo of myocardial ischemia based on findings of the indicator threshold comparisons.

9. A system according to claim 8, wherein the analysis module further assigns the weighted value comprising a highest weight to an ST segment elevation in the angina examination.

10. A method for automated diagnosis of myocardial ischemia through remote monitoring, comprising:

storing physiological measures comprising data either recorded on a regular basis by a medical device or derived therefrom;

matching qualitative measures associated with the physiological measures;

remotely identifying indications of myocardial ischemia, comprising;

examining the qualitative measures for angina; and

further evaluating the qualitative measures for one of a reduction in exercise capacity and of respiratory distress, which accompanies the angina;

determining a time course for each of the indications; and

forming a patient status comprising an onset of myocardial ischemia conditioned on the time course comprising a short duration.

11. A method according to claim 10, further comprising:

comparing each of the physiological measures against an indicator threshold comprising one of a finite cutoff value, weighted value, and statistical range; and

evaluating a potential onset, progression, regression, and status quo of myocardial ischemia based on findings of the indicator threshold comparisons.

12. A method according to claim 11, further comprising:

assigning the weighted value comprising a highest weight to an ST segment elevation in the angina examination.

13. A system for automated diagnosis of cardiac ischemia through ST segment monitoring, comprising:

a database module storing physiological measures comprising data either recorded on a regular basis by an implantable medical device or derived therefrom;

an analysis module determining indications of cardiac ischemia, by identifying the physiological measures that comprise electrocardial signals and detecting a period of increased activity indicated thereby, and determining a deviation in electrical potential during an ST segment of the electrocardial signal within the period of increased activity; and

a diagnostic module forming a patient status comprising a form of cardiac ischemia based on the deviation.

14. A system according to claim 13, wherein the analysis module further evaluates the deviation for one of an elevated potential and a depressed potential during the ST segment and further specifies the elevated potential as an indicator of the cardiac ischemia, wherein the form comprises myocardial ischemia.

15. A system according to claim 14, wherein the analysis module further confirms an absence of QRS duration of the electrocardial signal greater than 120 ms, and further declares the elevation of the ST segment as an a priori indicator of the myocardial ischemia when exceeding 2.0 mm.

16. A method for automated diagnosis of cardiac ischemia through ST segment monitoring, comprising:

storing physiological measures comprising data either recorded on a regular basis by an implantable medical device or derived therefrom;

determining indications of cardiac ischemia, comprising;

identifying the physiological measures that comprise electrocardial signals and detecting a period of increased activity indicated thereby; and

determining a deviation in electrical potential during an ST segment of the electrocardial signal within the period of increased activity; and

forming a patient status comprising a form of cardiac ischemia based on the deviation.

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

evaluating the deviation for one of an elevated potential and a depressed potential during the ST segment; and

specifying the elevated potential as an indicator of the cardiac ischemia, wherein the form comprises myocardial ischemia.

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

confirming an absence of QRS duration of the electrocardial signal greater than 120 ms; and

declaring the elevation of the ST segment as an a priori indicator of the myocardial ischemia when exceeding 2.0 mm.

19. A system for automated treatment of myocardial ischemia through ST segment monitoring, comprising:

a database module storing physiological measures comprising data either recorded on a regular basis by an implantable medical device or derived therefrom;

an analysis module determining indications of myocardial ischemia, by identifying the physiological measures that comprise electrocardial signals and detecting a period of increased activity indicated thereby, determining an elevation in electrical potential during an ST segment of the electrocardial signal within the period of increased activity, and delivering an intracardiac electrical therapy to treat the indications of myocardial ischemia in response to the elevation in electrical potential.

20. A system according to claim 19, wherein the analysis module further conforms an absence of QRS duration of the electrocardial signal greater than 120 ms, and further declares the elevation in electrical potential as an a priori indicator of the myocardial ischemia when exceeding 2.0 mm.

21. A system according to claim 19, wherein the analysis module further delivers a further therapy selected from the group comprising anticoagulation, antiplatelet drugs, beta-blockade, coronary vasodilators, afterload reduction, lipid lowering drugs, and mechanical therapies.

22. A method for automated treatment of myocardial ischemia through ST segment monitoring, comprising:

assembling physiological measures comprising data either recorded on a regular basis by an implantable medical device or derived therefrom;

determining indications of myocardial ischemia, comprising;

identifying the physiological measures that comprise electrocardial signals and detecting a period of increased activity indicated thereby; and

determining an elevation in electrical potential during an ST segment of the electrocardial signal within the period of increased activity; and

delivering an intracardiac electrical therapy to treat the indications of myocardial ischemia in response to the elevation in electrical potential.

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

confirming an absence of QRS duration of the electrocardial signal greater than 120 ms; and

declaring the elevation in electrical potential as an a priori indicator of the myocardial ischemia when exceeding 2.0 mm.

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

delivering a further therapy selected from the group comprising anticoagulation, antiplatelet drugs, beta-blockade, coronary vasodilators, afterload reduction, lipid lowering drugs, and mechanical therapies.