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Left ventricular dysfunction discriminated noninvasively beat by beat
Insights
This study introduces a noninvasive method using systolic time intervals and ballistocardiograms to identify dysfunctional heartbeats. The technique accurately distinguishes between normal and diseased heartbeats, offering a potentially useful prognostic index.
Area of Science:
- Cardiology
- Biomedical Engineering
- Noninvasive Diagnostics
Background:
- Left ventricular (LV) dysfunction detection is crucial for cardiac health.
- Noninvasive methods for identifying dysfunctional heartbeats are needed.
- Systolic time intervals (STI) and ballistocardiograms (BCG) offer potential diagnostic insights.
Purpose of the Study:
- To develop and validate a noninvasive method for discriminating between normal and dysfunctional left ventricular heartbeats.
- To assess the utility of systolic time intervals and ballistocardiograms in identifying cardiac dysfunction.
- To explore the relationship between respiratory cycles and cardiac mechanical function in healthy and diseased individuals.
Main Methods:
- Simultaneous recording of systolic time intervals (STI), acceleration ballistocardiograms (BCG), and respiratory cycles in healthy men and patients with myocardial infarction or hypertension.
- Analysis of 36 measurements per heartbeat, focusing on 9 primary variables identified through statistical methods.
- Application of a nonlinear quadratic discriminant function for beat-by-beat classification of heartbeats as 'normal' or 'coronary'.
Main Results:
- The ratio of preejection period to LV ejection time (ET) varied with respiration in normal men but not in those with cardiac conditions.
- A quadratic discriminant function achieved 87% accuracy in identifying normal heartbeats and 98% in identifying coronary heart disease (CHD) beats in a training group.
- Testing on older normal men and hypertensive men showed 89% and 67% 'normal' beat identification, respectively, with significant variability in 'coronary' beat detection across patient groups.
Conclusions:
- Noninvasive assessment using STI and BCG, analyzed with quadratic discriminant analysis, can effectively identify dysfunctional heartbeats.
- This beat-by-beat identification may serve as a sensitive and prognostically valuable index for cardiac health.
- The method demonstrates potential for noninvasive cardiac diagnostics, particularly in distinguishing between normal and pathological cardiac function.
Abstract:
To discriminate left ventricular (LV) dysfunctional beats noninvasively, simultaneous systolic time intervals (STI), acceleration ballistocardiograms (BCG) and respiratory cycle were recorded in 102 men with no history of cardiac disease and in 20 men with proved myocardial infarction or systemic hypertension. Thirty-six measurements were made on each heartbeat on a maximum of 20 beats per patient. The ratio of preejection period to LV ejection time (ET) varied significantly with the respiratory cycle in normal men, but not in men with proved myocardial infarctions or systemic hypertension. The BCG I-wave amplitude varied significantly with respiration in all 3 groups. Various statistical methods identified 9 primary variables of the 36, which differed significantly in a training group of 275 heartbeats in 19 normal, vs 46 beats in 5 coronary patients. A nonlinear quadratic discriminant function based on these primary variables identified 87% of the heartbeats as "normal" in the normal men and 98% as "coronary" in the coronary men. A test group of normal men older than 40 years showed 89% of 97 heartbeats "normal" and in hypertensive men 67% of 85 beats "normal." Comparison by patients showed a range of "coronary" beats in the training normal group from 0 to 50%, the older normal group 0 to 33%, and in the hypertensive patients 0 to 88%. The appropriate use of quadratic discriminant analysis to multivariable data may yield information not otherwise seen. A beat-by-beat identification of dysfunctional beats at rest may lead to a sensitive index that is prognostically useful.