AI-Enabled Electrocardiogram-Guided Guideline-Directed Medical Therapy on Incident Left Ve
This multicenter retrospective study evaluates whether artificial intelligence-enabled electrocardiography (AI-ECG) can identify individuals at high risk for left ventricular dysfunction and whether targeted guideline-directed medical therapy can mitigate subsequent risk. Using a large multicenter cohort of patients wi
| Condition(s) | Left Ventricular (LV) Systolic Dysfunction |
|---|---|
| Status | Recruiting |
| Phase | NA |
| Study type | Interventional |
| Summary | This multicenter retrospective study evaluates whether artificial intelligence-enabled electrocardiography (AI-ECG) can identify individuals at high risk for left ventricular dysfunction and whether targeted guideline-directed medical therapy can mitigate subsequent risk. Using a large multicenter cohort of patients with preserved left ventricular systolic function, the investigators applied an AI-ECG-based risk stratification approach and emulated a target trial to examine the association between guideline-directed therapies and the risk of incident left ventricular functional decline. |
| Who can participate | Inclusion Criteria: * With an ECG followed by an echocardiogram within a 90-day interval * With preserved left ventricular ejection fraction (LVEF ≥ 50%) Exclusion Criteria: * missing essential variables or ECG lead data * any prior LVEF \< 50% * loss to follow-up or death during the 90-day assessment window |
| Ages | 18 Years |
| Sex | All |
| Accepts healthy volunteers | Yes |
| Lead sponsor | Tri-Service General Hospital |
| Locations | Taipei, Taipei, Taiwan |
| Start date | 2026-01-01 |
| NCT ID | NCT07355023 |
| Official listing | https://clinicaltrials.gov/study/NCT07355023 |