Method and apparatus for prediction of sudden cardiac death by simultaneous assessment of autonomic function and cardiac electrical stability

• US 5,437,285 A
• Filed: 11/30/1993
• Issued: 08/01/1995
• Est. Priority Date: 02/20/1991
• Status: Expired due to Term

• Current Assignee: Georgetown University
• Original Assignee: Georgetown University
• Inventors: Verrier, Richard L., Nearing, Bruce D.
• Primary Examiner(s): Kamm, William E.
• Application Number:
  US08/159,504
• Time in Patent Office: 609 Days
• Field of Search: 128/702, 128/703, 128/704, 128/205
• US Class Current: 600/515
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/35 by template matching
• CPC Class Codes: A61B 5/355 Detecting T-waves
• CPC Class Codes: A61B 5/36 Detecting PQ interval, PR interval or QT interval
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/4035 Evaluating the autonomic nervous system
• CPC Class Codes: Y10S 128/925 Neural network

Abstract

A method and apparatus for predicting susceptibility to sudden cardiac death simultaneously assessing cardiac electrical stability and autonomic influence. Cardiac electrical stability is assessed by analyzing at least one of a beat-to-beat alternation in a T-wave of an ECG of a patient'"'"'s heart and dispersion of repolarization in the ECG of the patient'"'"'s heart. Autonomic influence on the patient'"'"'s heart is assessed by analyzing at least one of a magnitude of heart rate variability in the ECG of the patient'"'"'s heart and baroreceptor sensitivity.

Claims

1. A method of assessing cardiac vulnerability comprising the steps of:

sensing a plurality of ECG signals from a plurality of sites adjacent a heart;

analyzing an amplitude of beat-to-beat alternation in T-waves of successive R-R intervals of at least one of said ECG signals to obtain an alternans measure;

analyzing a magnitude of heart rate variability in successive R-R intervals of at least one of said ECG signals to obtain a heart rate variability measure;

analyzing a magnitude of dispersion of repolarization in a QT interval across at least two of said plurality of ECG signals to obtain a dispersion measure; and

simultaneously analyzing said alternans measure, said heart rate variability measure and said dispersion measure to assess cardiac vulnerability.

2. The method of claim 1, wherein said step of sensing a plurality of ECG signals comprises, for each ECG signal:

placing a precordial ECG lead on the surface of a subject'"'"'s body proximate to the subject'"'"'s heart to sense said ECG signal;

amplifying said ECG signal;

low-pass filtering said ECG signal; and

sampling said ECG signal.

3. The method of claim 1, wherein said step of analyzing an amplitude of beat-to-beat alternation comprises:

selecting at least one of said plurality of ECG signals;

predicting the location in said ECG signal of a T-wave in each R-R interval;

partitioning each T-wave in said ECG signal into a plurality of time divisions;

summing the samples in each of said time divisions of said selected ECG signal;

forming a time series for each of said time divisions, each time series including corresponding sums from corresponding time divisions from successive ones of said T-waves; and

performing dynamic estimation on each said time series to estimate the amplitude of beat-to-beat alternation for each said time division.

4. The method of claim 1, wherein said step of analyzing a magnitude of heart rate variability comprises:

selecting at least one of said plurality of ECG signals;

locating the peak amplitude in each R-R interval to find the apex of each R-wave in said selected ECG signal;

calculating the time between successive R-waves to determine a magnitude of each said R-R interval;

forming a time series with said magnitudes of said R-R intervals;

performing dynamic estimation on said time series to estimate a magnitude of a high frequency component of heart rate variability and to estimate a magnitude of a low frequency component of heart rate variability; and

forming a ratio of said magnitudes of said low frequency and said high frequency components of heart rate variability, said ratio indicating sympathetic activity.

5. The method of claim 1, wherein said step of analyzing dispersion of repolarization comprises:

for each of said plurality of ECG signals,

locating the peak amplitude in each R-R interval to find the apex of each R-wave,

determining the temporal location of the beginning of each Q-wave based on the apex of each R-wave,

determining the temporal location of the end of each T-wave, and

calculating each QT interval as a time difference from the beginning of the Q-wave to the end of the T-wave; and

estimating a measure of dispersion of repolarization of said QT intervals across said plurality of ECG signals.

6. The method of claim 5, wherein said step of estimating a measure of dispersion comprises:

calculating a maximum difference between said QT intervals taken across said plurality of ECG signals to estimate said measure of dispersion.

7. The method of claim 5, wherein said step of estimating a measure of dispersion comprises:

calculating each R-R interval as a time difference between successive R-waves;

using each R-R interval to correct a corresponding QT interval to produce a corrected QT interval for each QT interval; and

calculating a maximum difference between said corrected QT intervals taken across said plurality of ECG signals to estimate said measure of dispersion.

8. The method of claim 5, wherein said step of estimating a measure of dispersion comprises:

averaging said QT intervals to produce an average QT interval;

dividing each QT interval by said average QT interval to produce a QT ratio for each QT interval;

averaging said QT ratios to produce an average QT ratio; and

calculating a standard deviation of said QT ratio to estimate said measure of dispersion.

9. The method of claim 5, wherein said step of estimating a measure of dispersion comprises:

calculating each R-R interval as a time difference between successive R-waves;

using each R-R interval to correct a corresponding QT interval to produce a corrected QT interval for each QT interval;

averaging said corrected QT intervals to produce an average corrected QT interval;

dividing each corrected QT interval by said average corrected QT interval to produce corrected QT ratios;

averaging said corrected QT ratios to produce an average corrected QT ratio; and

calculating a standard deviation of said corrected QT ratio to estimate said measure of dispersion.

10. The method of claim 5, wherein said step of estimating a measure of dispersion comprises:

calculating, for each R-R interval across said plurality of ECG signals, an average ECG signal;

calculating, for each R-R interval of said plurality of ECG signals, an RMS deviation using said average ECG signal; and

taking an amplitude of a maximum one of said RMS deviations as said measure of dispersion.

11. The method of claim 1, further comprising the step of:

analyzing instantaneous heart rate, arterial blood pressure and instantaneous lung volume to obtain a measure of baroreceptor sensitivity, and

wherein said step of simultaneously analyzing further includes analyzing said measure of baroreceptor sensitivity to assess cardiac vulnerability.

12. The method of claim 11, wherein said step of analyzing instantaneous heart rate, arterial blood pressure and instantaneous lung volume comprises:

(1) selecting at least one of said plurality of ECG signals;

(2) sensing and digitizing a blood pressure signal representing arterial blood pressure;

(3) sensing and digitizing a respiration signal representing instantaneous lung volume;

(4) computing an instantaneous heart rate for each R-R interval in said selected ECG signal; and

(5) using said heart rate, said blood pressure signal and said respiration signal to determine said measure of baroreceptor sensitivity.

13. A method of predicting susceptibility to sudden cardiac death, comprising the steps of:

(a) analyzing at least one of a beat-to-beat alternation in a T-wave of an ECG of a patient'"'"'s heart and dispersion of repolarization in said ECG of the patient'"'"'s heart to assess cardiac electrical stability; and

(b) analyzing at least one of a magnitude of heart rate variability in said ECG of the patient'"'"'s heart and baroreceptor sensitivity to assess autonomic influence on the patient'"'"'s heart, provided that alternation and heart rate variability are not analyzed in combination without at least one of dispersion and baroreceptor sensitivity also being analyzed; and

(c) performing steps (a) and (b) simultaneously to assess the patient'"'"'s risk of sudden cardiac death.

14. The method of claim 13, wherein said step (a) of analyzing comprises:

analyzing both beat-to-beat alternation and dispersion of repolarization to assess cardiac electrical stability.

15. The method of claim 14 wherein said step (b) of analyzing comprises:

analyzing both said magnitude of heart rate variability and said baroreceptor sensitivity to assess autonomic influence on the heart.

16. The method of claim 14 wherein said step of analyzing beat-to-beat alternation, comprises:

(1) sensing an ECG signal from the patient'"'"'s heart, said ECG signal having a plurality of R-R intervals;

(2) digitizing said ECG signal;

(3) predicting the location in said ECG signal of said T-wave in each R-R interval;

(4) partitioning each T-wave in said ECG signal into a plurality of time divisions;

(5) summing the samples in each of said time divisions of said ECG signal;

(6) forming a time series for each of said time divisions, each time series including corresponding sums from corresponding time divisions from successive ones of said T-waves; and

(7) performing dynamic estimation on each said time series to estimate the amplitude of beat-to-beat alternation for each said time division.

17. The method of claim 16 wherein said step of analyzing dispersion of repolarization comprises:

(1) sensing a plurality of ECG signals from a plurality of sites adjacent a heart, each of said plurality of ECG signals having a plurality of R-R intervals;

(2) for each of said plurality of ECG signals,

i) locating the peak amplitude in each R-R interval to find the apex of each R-wave,

ii) determining the temporal location of the beginning of each Q-wave based on the apex of each R-wave,

iii) determining the temporal location of the end of each T-wave, and

iv) calculating each QT interval as a time difference from the beginning of the Q-wave to the end of the T-wave; and

(3) estimating a measure of dispersion of repolarization of said QT intervals across said plurality of ECG signals.

18. The method of claim 17 wherein said step (b) of analyzing comprises:

analyzing both said magnitude of heart rate variability and said baroreceptor sensitivity to assess autonomic influence on the heart.

19. The method of claim 18, wherein said step of analyzing heart rate variability comprises:

(1) sensing an ECG signal from the patient'"'"'s heart, said ECG signal having a plurality of R-R intervals;

(2) digitizing said ECG signal;

(3) locating the peak amplitude in each R-R interval to find the apex of each R-wave in said ECG signal;

(4) calculating the time between successive R-waves to determine a magnitude of each said R-R interval;

(5) forming a time series with said magnitudes of said R-R intervals;

(6) performing dynamic estimation on said time series to estimate a magnitude of a high frequency component of heart rate variability and to estimate a magnitude of a low frequency component of heart rate variability; and

(7) forming a ratio of said magnitudes of said low frequency and said high frequency components of heart rate variability, said ratio indicating sympathetic activity.

20. The method of claim 19, wherein said step of analyzing baroreceptor sensitivity comprises:

(1) sensing and digitizing an ECG signal from the patient'"'"'s heart, said ECG signal having a plurality of R-R intervals;

(2) sensing and digitizing a blood pressure signal representing arterial blood pressure;

(3) sensing and digitizing a respiration signal representing instantaneous lung volume;

(4) computing an instantaneous heart rate for each R-R interval in said ECG signal; and

(5) using said heart rate, said blood pressure signal and said respiration signal to determine said baroreceptor sensitivity.

21. The method of claim 13, wherein said step (b) of analyzing comprises:

analyzing both said magnitude of heart rate variability and said baroreceptor sensitivity to assess autonomic influence on the heart.

22. An apparatus for predicting susceptibility to sudden cardiac death, comprising:

first means for analyzing at least one of a beat-to-beat alternation in a T-wave of an ECG of a patient'"'"'s heart and dispersion of repolarization in said ECG of the patient'"'"'s heart to assess cardiac electrical stability; and

second means for analyzing at least one of a magnitude of heart rate variability in said ECG of the patient'"'"'s heart and baroreceptor sensitivity to assess autonomic influence on the patient'"'"'s heart, provided that alternation and heart rate variability are not analyzed in combination with at least one of dispersion and baroreceptor sensitivity also be analyzed; and

third means for simultaneously analyzing assessment of cardiac electrical stability from said first means and autonomic influence on the patient'"'"'s heart from said second means to predict the patient'"'"'s risk of sudden cardiac death.

23. The apparatus of claim 22, wherein said first means comprises:

fourth means for analyzing beat-to-beat alternation to assess cardiac electrical stability; and

fifth means for analyzing dispersion of repolarization to assess cardiac electrical stability.

24. The apparatus of claim 23, wherein said second means comprises:

sixth means for analyzing said magnitude of heart rate variability to assess autonomic influence on the heart; and

seventh means for analyzing said magnitude of heart rate variability to assess autonomic influence on the heart.

25. The apparatus of claim 24, further comprising:

means for sensing a plurality of ECG signals from a plurality of sites adjacent a heart, each of said plurality of ECG signals having a plurality of R-R intervals; and

means for digitizing said plurality of ECG signals.

26. The apparatus of claim 25, wherein said fourth means comprises:

means for predicting the location in a selected ECG signal of a T-wave in each R-R interval;

means for partitioning each T-wave in said selected ECG signal into a plurality of time divisions;

means for summing the samples in each of said time divisions of said selected ECG signal;

means for forming a time series for each of said time divisions, each time series including corresponding sums from corresponding time divisions from successive ones of said T-waves; and

means for dynamically estimating on each said time series to estimate the amplitude of beat-to-beat alternation for each said time division.

27. The apparatus of claim 26, wherein said fifth means comprises:

means for locating the peak amplitude in each R-R interval to find the apex of each R-wave in each of said plurality of ECG signals;

means for determining the temporal location of the beginning of each Q-wave based on the apex of each R-wave;

means for determining the temporal location of the end of each T-wave;

means for calculating each QT interval as a time difference from the beginning of the Q-wave to the end of the T-wave; and

means for estimating a measure of dispersion of repolarization of said QT intervals across said plurality of ECG signals.

28. The apparatus of claim 27, wherein said sixth means comprises:

means for locating the peak amplitude in each R-R interval of a selected ECG signal to find the apex of each R-wave;

means for calculating the time between successive R-waves to determine a magnitude of each said R-R interval;

means for forming a time series with said magnitudes of said R-R intervals;

means for performing dynamic estimation on said time series to estimate a magnitude of a high frequency component of heart rate variability and to estimate a magnitude of a low frequency component of heart rate variability; and

means for forming a ratio of said magnitudes of said low frequency and said high frequency components of heart rate variability, said ratio indicating sympathetic activity.

29. The apparatus of claim 28, wherein said seventh means comprises:

sensing and digitizing a blood pressure signal representing arterial blood pressure;

sensing and digitizing a respiration signal representing instantaneous lung volume;

computing an instantaneous heart rate for each R-R interval in a selected ECG signal; and

using said heart rate, said blood pressure signal and said respiration signal to determine said baroreceptor sensitivity.