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Last Posted: Mar 14, 2024
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An ECG-based artificial intelligence model for assessment of sudden cardiac death risk
L Holmstrom et al, Comm Med, February 2024

From the abstract: " Conventional ECG-based algorithms could contribute to sudden cardiac death (SCD) risk stratification but demonstrate moderate predictive capabilities. Deep learning (DL) models use the entire digital signal and could potentially improve predictive power. We aimed to train and validate a 12?lead ECG-based DL algorithm for SCD risk assessment. The DL model achieves an AUROC of 0.889 (95% CI 0.861–0.917) for the detection of SCD cases vs. controls in the internal held-out test dataset, and is successfully validated in external SCD cases with an AUROC of 0.820 (0.794–0.847). "

The burden of splice-disrupting variants in inherited heart disease and unexplained sudden cardiac death
ES Singer et al, NPJ Genomic Medicine, October 11, 2023

From the abstract: "We performed burden testing of rare splice-disrupting variants in people with inherited heart disease and sudden unexplained death compared to 125,748 population controls. ClinGen definitively disease-associated inherited heart disease genes were amplified using RNA extracted from fresh blood, derived cardiomyocytes, and myectomy tissue. Variants were functionally assessed and classified for pathogenicity. We found 88 in silico-predicted splice-disrupting variants in 128 out of 1242 (10.3%) unrelated participants. "

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