The CNN-based single-lead ECG device demonstrated excellent diagnostic accuracy for detecting heart failure in primary care, achieving an AUC of 0.905.
Cohort (n=112)
No
Does a CNN-based single-lead electrocardiographic device accurately diagnose heart failure in Japanese patients presenting with dyspnea or lower leg edema in primary care settings?
A CNN-based single-lead ECG device demonstrated high diagnostic accuracy (AUC 0.905) for detecting heart failure in Japanese primary care patients presenting with dyspnea or edema.
Effect estimate: AUC 0.905 (95% CI 0.846-0.964)
Abstract The applicability of existing Convolutional Neural Network (CNN) models for diagnosing heart failure in Japanese patients remains unclear. We aimed to evaluate the accuracy of a CNN-based single-lead electrocardiographic device for point-of-care heart failure screening in primary care settings. We included patients aged ≥ 20 years with a chief complaint of dyspnea or lower leg edema. A single-lead electrocardiogram was recorded, following which a CNN-based algorithm derived a quantitative index of heart failure severity (HF index). The primary endpoint was the diagnostic accuracy of the HF index. Secondary endpoints included identifying factors affecting the diagnostic performance and accuracy of the HF index in classifying heart failure phenotypes and disease severity. We enrolled 112 patients, including 50 patients with heart failure. The HF index had excellent diagnostic performance, with an area under the receiver operating characteristic curve of 0.905. Its sensitivity and specificity for heart failure diagnosis were 0.800 and 0.871, respectively. No significant interactions were observed with the HF index for several evaluated factors. The HF index exhibited strong predictive ability for heart failure phenotypes and disease severity. In older Japanese patients, the single-lead electrocardiographic device enabled simple and accessible screening for different heart failure phenotypes in primary care setting. Trial registration: This manuscript reports the results of a clinical study registered with UMIN-CTR (UMIN000057871) on May 15, 2025.
August 12 publication; buzz in digital health cardiology communities; potential for widespread adoption.
Hori et al. (Wed,) conducted a cohort in Heart failure (n=112). CNN-based single-lead electrocardiographic device (SHINDENKUN) vs. Standard clinical diagnosis was evaluated on Diagnostic accuracy of the HF index for heart failure (AUC) (AUC 0.905, 95% CI 0.846-0.964). The CNN-based single-lead ECG device demonstrated excellent diagnostic accuracy for detecting heart failure in primary care, achieving an AUC of 0.905.
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