Artificial Intelligence Applied to Echocardiography for Detection of Heart Failure with Preserved Ejection Fraction and Elevated Filling Pressures: A Diagnostic Test Accuracy Meta-Analysis
Heart failure with preserved ejection fraction (HFpEF) accounts for nearly half of heart failure cases and remains difficult to diagnose non-invasively. Artificial intelligence (AI) applied to echocardiography may improve detection, but its aggregate diagnostic accuracy has not been quantified. We performed a diagnostic test accuracy meta-analysis of AI-enabled echocardiography for identifying HFpEF, elevated left ventricular filling pressure, or diastolic dysfunction. MEDLINE/PubMed, Embase, and CENTRAL were se…
Pooled across eight studies, AI applied to echocardiography detected HFpEF and elevated filling pressures with roughly 84% sensitivity and 83% specificity, offering a non-invasive route for a condition that is hard to diagnose.
Heterogeneity across the included studies was high and accuracy varied significantly by reference standard, so the authors call for larger, prospectively validated studies before routine clinical adoption.
Evidence
- Peer-reviewedCardiology in Review2026-10-29
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Truvace Impact Record TRV-2026-2311, v1: “Artificial Intelligence Applied to Echocardiography for Detection of Heart Failure with Preserved Ejection Fraction and Elevated Filling Pressures: A Diagnostic Test Accuracy Meta-Analysis.” Truvace, 2026-10-29. /record/TRV-2026-2311 (accessed at citation time). sha256 987f2dadb0f3983a…
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