Evidence map›Paper›PMID 42216678›Full record

ArticleEuropace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology2026

Sex-specific virtual population for the prediction and assessment of arrhythmia risk.

Fengze Sui, Dasen Yan, Xiangbin Meng, Chengxiang Duan, Yucheng Zhang, Wen Gao, Zhen Song

Abstract read
In one paragraph

Article in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Fengze SuiSchool of Computer Science and Technology, Harbin Institute of Technology, HIT Campus, Shenzhen University Town, Nanshan District, Shenzhen 518055, Guangdong, China.ORCID 0009-0002-4619-5539
Dasen YanPengcheng Laboratory, No. 2 Xingke 1st Street, Nanshan District, Shenzhen 518000, Guangdong, China.ORCID 0000-0002-5834-0396
Xiangbin MengPengcheng Laboratory, No. 2 Xingke 1st Street, Nanshan District, Shenzhen 518000, Guangdong, China.
Chengxiang DuanThomas Lord Department of Computer Science, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA.
Yucheng ZhangPengcheng Laboratory, No. 2 Xingke 1st Street, Nanshan District, Shenzhen 518000, Guangdong, China.ORCID 0000-0002-9300-2632
Wen GaoSchool of Computer Science and Technology, Harbin Institute of Technology, HIT Campus, Shenzhen University Town, Nanshan District, Shenzhen 518055, Guangdong, China.ORCID 0000-0001-8894-1806
Zhen SongPengcheng Laboratory, No. 2 Xingke 1st Street, Nanshan District, Shenzhen 518000, Guangdong, China.

Funding

National Natural Science Foundation of ChinaNSFC 82172067
6 · The paper itself

Abstract

aimsWomen are at higher risk of serious ventricular arrhythmias, including torsades de pointes, 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 AND

resultsWe constructed male and female virtual cohorts using a one-dimensional 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. Proarrhythmic risk was defined by tissue-scale instability events (premature ventricular complexes, T-wave alternans, or repolarization failure). Drivers were analysed using regression and channel-sensitivity analysis, and clinical 24 h concentration-ECG data after dosing were used for external validation. 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 24 h clinical ECG data for key reference drugs.

conclusionSex-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.

Indexed as

Arrhythmias, CardiacHeart Conduction SystemLong QT SyndromeModels, CardiovascularAction PotentialsComputer SimulationElectrocardiographyFemaleHeart RateHumansMalePredictive Value of TestsRisk AssessmentRisk FactorsSex FactorsDrug-induced arrhythmiaIn silico trialLong QT syndromeSex hormonesSex stratificationVirtual population

Identifiers

PMID42216678
PMCPMC13317967

What Socratic holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.