Key result
AI-ECG detects GLS-defined subclinical LV dysfunction in hypertensive adults with an AUC of 0.86.
Why the study?
Speckle-tracking echocardiography to detect subclinical LV impairment is not universally available, so the diagnostic capability of AI-ECG was evaluated.
Does an artificial intelligence-enhanced ECG algorithm accurately detect GLS-defined subclinical left ventricular dysfunction in hypertensive adults with preserved LVEF?
Observational (n=348)
No
Does an artificial intelligence-enhanced ECG algorithm accurately detect GLS-defined subclinical left ventricular dysfunction in hypertensive adults with preserved LVEF?
Effect estimate: AUC 0.86, Adjusted OR 1.12 per 0.1 increase in AI-ECG probability score (95% CI 95% CI for AUC 0.82–0.89; 95% CI for OR 1.07–1.18)
Absolute Event Rate: 0.61% vs 0.29%
p-value: p=<0.001
An AI-enhanced ECG algorithm can accurately identify subclinical left ventricular dysfunction in hypertensive patients with preserved ejection fraction, offering a scalable and accessible tool for early risk stratification.
Supports scalable subclinical LV dysfunction screening in hypertensive patients with preserved LVEF; extends AI-ECG utility but remains hypothesis-generating pending prospective validation.
Background Subclinical left ventricular (LV) impairment—characterized by reduced global longitudinal strain (GLS) despite normal left ventricular ejection fraction (LVEF)—is frequently encountered in hypertensive patients. While speckle-tracking echocardiography is the standard method for detecting early myocardial dysfunction, it is not universally available. Artificial intelligence–enhanced electrocardiography (AI-ECG) has emerged as a promising tool capable of uncovering subtle electrical patterns linked to early myocardial impairment. This study investigates the diagnostic capability of AI-ECG for detecting GLS-defined subclinical LV dysfunction. Methods In this retrospective analysis, 348 hypertensive adults who underwent both ECG and echocardiography within the same clinical visit (2022–2024) were evaluated. Subclinical LV dysfunction was defined as LVEF ≥50% and GLS > −18%.A convolutional neural network–based AI algorithm generated an AI-ECG probability score (range 0–1) representing the likelihood of LV dysfunction. Statistical analyses included correlation testing, regression modeling, and ROC curve evaluation. Results Subclinical LV dysfunction was identified in 134 participants (38.5%). The AI-ECG probability score differed markedly between the abnormal GLS group and the normal GLS group (0.61 ± 0.20 vs. 0.29 ± 0.18; p < 0.001). GLS values demonstrated a strong negative association with AI-ECG scores (r = –0.63). ROC analysis showed robust diagnostic ability with an AUC of 0.86 (95% CI: 0.82–0.89). In multivariable logistic regression adjusting for LV mass index, E/e′, age, and hypertension duration, the AI-ECG probability score remained independently associated with subclinical LV dysfunction (adjusted OR 1.12 per 0.1 increase, 95% CI 1.07–1.18; p < 0.001). Conclusion AI-ECG accurately detects GLS-defined subclinical LV dysfunction in hypertensive adults and may serve as an accessible tool for early risk stratification in routine clinical settings.
No takes yet. Share an insight, caveat, or question.
Muhammet Fatih Bayraktar (2026) conducted an observational in Hypertensive adults with preserved left ventricular ejection fraction (LVEF ≥ 50%) undergoing evaluation for subclinical left ventricular dysfunction defined by impaired global longitudinal strain (GLS > -18%) (n=348). Artificial intelligence–enhanced electrocardiography (AI-ECG) vs. GLS-defined subclinical LV dysfunction by speckle-tracking echocardiography was evaluated on Detection of GLS-defined subclinical left ventricular dysfunction (GLS > -18% with preserved LVEF) by AI-ECG probability score (AUC 0.86, Adjusted OR 1.12 per 0.1 increase in AI-ECG probability score, 95% CI 95% CI for AUC 0.82–0.89; 95% CI for OR 1.07–1.18, p=<0.001). Artificial intelligence–enhanced ECG detected GLS-defined subclinical left ventricular dysfunction with an AUC of 0.86 and an adjusted OR of 1.12 per 0.1 increase in AI-ECG probability score in hypertensive adults with preserved LVEF.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: