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Related Experiment Videos

Left ventricular dysfunction discriminated noninvasively beat by beat.

A G Dinaburg, B R Zuckerman

    The American Journal of Cardiology
    |January 1, 1984
    PubMed
    Summary
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    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.

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  • 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.