Sex-specific virtual population for the prediction and assessment of arrhythmia risk
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ID: 315402
2026
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Abstract
BACKGROUND AND AIMS: Women are at higher risk of serious ventricular arrhythmias, including torsades de pointes (TdP), when repolarization reserve is reduced, but sex-stratified mechanisms and quantitative risk assessment remain challenging. We aimed to develop scalable, tissue-scale, sex-aware ventricular virtual populations to quantify and explain sex differences in inherited and acquired proarrhythmic susceptibility. METHODS: We constructed male and female virtual cohorts using a one-dimensional (1D) ventricular cable model with pseudo-electrocardiogram (pseudo-ECG), integrating sex-specific ionic conductance backgrounds and acute sex-hormone modulation. Virtual populations were filtered under multi-condition stress tests and calibrated to clinical corrected QT interval (QTc) distributions. We generated long QT syndrome types 1-3 (LQT1-3) cohorts, simulated sympathetic stress, and performed virtual drug trials for 109 compounds using multichannel block profiles at 1× effective free therapeutic plasma concentration (EFTPC). Proarrhythmic risk was defined by tissue-scale instability events (premature ventricular complexes, T-wave alternans, or repolarization failure). Drivers were analyzed using regression and channel-sensitivity analysis, and clinical 24h concentration-electrocardiogram (ECG) data after dosing were used for external validation. RESULTS: The female cohorts exhibited higher simulated event risk across long QT syndrome subtypes and across multichannel drug block profiles, including drugs with <10 ms mean QTc prolongation. Female-to-male risk ratios tracked clinical risk categories. Simulated QTc time-courses and concentration-QTc trends agreed with 24h clinical ECG data for key reference drugs. CONCLUSIONS: Sex-aware tissue-scale virtual populations enable in silico trials that quantify proarrhythmic risk beyond mean ΔQTc, provide mechanistic drivers, and support sex-informed cardiac safety evaluation and monitoring strategies.
| Reference Key |
openalex_W7162855198
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| Authors | Fengze Sui, Dasen Yan, Xiangbin Meng, Chengxiang Duan, Yu Zhang, Wen Gao, Zhen Song |
| Journal | EP Europace |
| Year | 2026 |
| DOI |
10.1093/europace/euag133
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| URL | |
| Keywords | Keywords not found |
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