Sebastian Emmanuel Willyanto, Imke Maria Del Rosario Puling, Nyoman Deva Pramana Giri, Jesphine Arbi Wijaya, Liliana Dewi, Derren David Christian Homenta Rampengan, Valerinna Yogibuana Swastika Putri
Background: With over 260,000 yearly mortality, 87% from low socio-economic countries, congenital heart disease (CHD) stands as a major global health crisis. Echocardiography, the current diagnostic standardized approach, often delays diagnosis due to interpretation variability and limited availability in low socioeconomic countries. Hence, exploring alternative screening approaches is crucial. The deep learning (DL) method coupled with heart sound analysis is a promising diagnostic approach for early CHD detection. Objectives: This study focuses on the innovation of DL-based heart sound analysis in enhancing the diagnosis of CHD patients. Methods: The outcomes of interest of the study were the sensitivity, specificity, and area under the curve (AUC) of various diagnostic tools and DL methods used in diagnosing CHD. Quality appraisal was done using Quality Assessment of Diagnostic Accuracy Studies 2, while the diagnostic meta-analysis used Stata MP 17. Results: A comprehensive search across seven databases yielded 19 articles for analysis. Among these, 13 were deemed low-risk and six unclear-risk of bias. The results were observed through meta-analysis with sensitivity at 91% (95% confidence interval [CI] = 0.85–0.94, P = 0.001), specificity at 92% (95% CI = 0.86–0.95, P = 0.001), and an AUC of 96% (95% CI = 0.94–0.98). Conclusions: The adoption of DL-based heart sound analysis for CHD diagnosis shows promise, demonstrating good diagnostic accuracy and potential as an adjunctive tool to support triage or pre-screening, although further validation is required before it can be considered alongside echocardiography. © 2026 Annals of Pediatric Cardiology.
Faculty of Medicine, Clinical Clerkship Program, Universitas Brawijaya, Saiful Anwar Regional General Hospital, Malang, Indonesia; Faculty of Medicine, Clinical Clerkship Program, Universitas Sam Ratulangi, R.D. Kandou Central General Hospital, Manado, Indonesia; Department of Cardiology and Vascular Medicine, Brawijaya Cardiovascular Research Center, Faculty of Medicine, Universitas Brawijaya, Universitas Brawijaya, Malang, Indonesia
