Key result
An automatic detection algorithm using a single lead ECG differentiated patients with left ventricular hypertrophy from healthy volunteers using S-wave amplitude (p=0.01) and ST-segment (p=0.04).
Why the study?
Does an automatic detection algorithm using single lead ECG differentiate between LVH patients and healthy volunteers?
Does an automatic detection algorithm using single lead ECG differentiate between LVH patients and healthy volunteers?
p-value: p=0.01 and 0.04
An automatic detection algorithm using single-lead ECG can significantly differentiate between patients with LVH and healthy volunteers, showing potential for application in wearable heart monitors.
In this letter, an automatic detection algorithm for hypertrophic cardiomyopathy (HCM) is presented. Of particular interest is the algorithm's ability to differentiate HCM subjects and healthy volunteers from a single lead ECG dataset. Suspected HCM subjects are identified by the primary clinical abnormality associated with HCM: left ventricular hypertrophy (LVH). In total, n = 43 human subjects ECG datasets are investigated: n = 21 healthy volunteers and n = 22 LVH patients. Significant differences of p-value 0.01 and 0.04 were found for the respective ECG parameters, i.e., S-wave amplitude and ST-segment, when differentiating between the LVH patients and healthy human volunteers.
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Denis et al. (2021) conducted a letter in Hypertrophic cardiomyopathy (n=43). Automatic detection algorithm using a single lead ECG vs. Healthy volunteers was evaluated on Differentiation of ECG parameters (S-wave amplitude and ST-segment) (p=0.01 and 0.04). An automatic detection algorithm using a single lead ECG differentiated patients with left ventricular hypertrophy from healthy volunteers using S-wave amplitude (p=0.01) and ST-segment (p=0.04).
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