医学
内科学
心脏病学
植入式心律转复除颤器
射血分数
肥厚性心肌病
室性心动过速
危险系数
心源性猝死
荟萃分析
心肌病
心力衰竭
置信区间
作者
Sotirios Chiotis,Ioannis Doundoulakis,Aikaterini Zgouridou,Christos Piperis,Dimitrios Raptis,Aliki Peletidi,Aikaterini Vassilikou,Maria Toumpourleka,Fotios Economou,Aristi Boulmpou,V. Vassilikos,Γεώργιος Γιαννόπουλος
标识
DOI:10.1093/ehjqcco/qcaf021
摘要
Abstract Background Hypertrophic cardiomyopathy (HCM) is a common genetic cardiac disorder and a leading cause of sudden cardiac death (SCD). Implantable cardioverter-defibrillators (ICDs) are critical for SCD prevention, but risk stratification remains challenging. Objective To evaluate the predictive performance of conventional risk factors for arrhythmic events in HCM patients with ICDs. Methods We conducted a systematic search of PubMed, Cochrane Central Register of Controlled Trials (CENTRAL) and Clinical Trials from inception to November 2024, including studies reporting hazard ratios (HRs) for clinical, electrocardiographic, and imaging predictors of arrhythmic events in ICD recipients with HCM. Pooled HRs were calculated using random-effects model. Results 12 studies of 3,297 HCM patients with ICDs (91% primary prevention, 9% secondary prevention) were included, with a mean age of 50 years. The annual arrhythmic event rate was 5% (95% CI: 4–7%) during a mean follow-up of 4 years. Significant predictors of arrhythmic events included non-sustained ventricular tachycardia (NSVT) (HR: 2.19, 95% CI: 1.62–2.98), left ventricular ejection fraction (LVEF) < 50% (HR: 1.91, 95% CI: 1.27–2.89), intraventricular pressure gradient (IVPG) > 30 mmHg (HR: 1.92, 95% CI: 1.03–3.56), and secondary prevention indication (HR: 2.18, 95% CI: 1.39–3.41). Sensitivity analysis in the primary prevention subgroup confirmed NSVT and LVEF < 50% as consistently significant predictors, while other traditional risk factors showed limited predictive value. Conclusion Specific markers remain strong predictors of arrhythmic events in HCM patients with ICDs, but other traditional risk factors may lack predictive utility.
科研通智能强力驱动
Strongly Powered by AbleSci AI