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TRV-2026-0937Certified recordPeer-reviewed

Ai-based multimodal analysis of ECG and clinical data for evaluation for competitive sports participation: The VALETUDO trial

Aims Pre-participation cardiovascular screening (PPS) is essential for preventing SCD in athletes, yet ECG interpretation requires expertise and remains resource-intensive. We aimed to evaluate the feasibility and diagnostic performance of a deep learning (DL) model for analysis of clinical data and resting 12‑lead ECG obtained during routine PPS in competitive athletes. Methods In this prospective single center observational study, competitive athletes aged 18 to 60 years and undergoing routine PPS were enrolle…

Health · G Space — documented gain · certified 2026-08-31 · v1 · article view · machine-readable

Current reading — gain

A multimodal deep learning model analyzing resting 12-lead ECG and clinical data was feasible for pre-participation cardiovascular screening and achieved moderate discrimination for fitness for competitive sports.

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Single-center design with 526 athletes and no external validation, requiring wider experience before clinical use.

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Truvace Impact Record TRV-2026-0937, v1: “Ai-based multimodal analysis of ECG and clinical data for evaluation for competitive sports participation: The VALETUDO trial.” Truvace, 2026-08-31. /record/TRV-2026-0937 (accessed at citation time). sha256 50829e4a880ab678…

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