Wang Meng, Peterson Derick R, Pagan Eleonora, Bagnardi Vincenzo, Mazzanti Andrea, McNitt Scott, Rich David Q, Seplaki Christopher L, Kutyifa Valentina, Polonsky Bronislava, Barsheshet Alon, Kukavica Deni, Rosero Spencer, Goldenberg Ilan, Priori Silvia, Zareba Wojciech
Division of Cardiology, Clinical Cardiovascular Research Center, University of Rochester Medical Center, Rochester, NY, United States.
Division of Epidemiology, Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, United States.
Front Cardiovasc Med. 2022 Oct 7;9:988951. doi: 10.3389/fcvm.2022.988951. eCollection 2022.
Risk stratification in long QT syndrome (LQTS) patients is important for optimizing patient care and informing clinical decision making. We developed a risk prediction algorithm with prediction of 5-year absolute risk of the first life-threatening arrhythmic event [defined as aborted cardiac arrest, sudden cardiac death, or appropriate implantable cardioverter defibrillator (ICD) shock] in LQTS patients, accounting for individual risk factors and their changes over time.
Rochester-based LQTS Registry included the phenotypic cohort consisting of 1,509 LQTS patients with a QTc ≥ 470 ms, and the genotypic cohort including 1,288 patients with single LQT1, LQT2, or LQT3 mutation. We developed two separate risk prediction models which included pre-specified time-dependent covariates of beta-blocker use, syncope (never, syncope while off beta blockers, and syncope while on beta blockers), and sex by age < and ≥13 years, baseline QTc, and genotype (for the genotypic cohort only). Follow-up started from enrollment in the registry and was censored at patients' 50s birthday, date of death due to reasons other than sudden cardiac death, or last contact, whichever occurred first. The predictive models were externally validated in an independent cohort of 1,481 LQTS patients from Pavia, Italy.
In Rochester dataset, there were 77 endpoints in the phenotypic cohort during a median follow-up of 9.0 years, and 47 endpoints in the genotypic cohort during a median follow-up of 9.8 years. The time-dependent extension of Harrell's generalized C-statistics for the phenotypic model and genotypic model were 0.784 (95% CI: 0.740-0.827) and 0.785 (95% CI: 0.721-0.849), respectively, in the Rochester cohort. The C-statistics obtained from external validation in the Pavia cohort were 0.700 (95% CI: 0.610-0.790) and 0.711 (95% CI: 0.631-0.792) for the two models, respectively. Based on the above models, an online risk calculator estimating a 5-year risk of life-threatening arrhythmic events was developed.
This study developed two risk prediction algorithms for phenotype and genotype positive LQTS patients separately. The estimated 5-year absolute risk can be used to quantify a LQTS patient's risk of developing life-threatening arrhythmic events and thus assisting in clinical decision making regarding prophylactic ICD therapy.
长QT综合征(LQTS)患者的风险分层对于优化患者护理和指导临床决策至关重要。我们开发了一种风险预测算法,用于预测LQTS患者首次发生危及生命的心律失常事件(定义为心脏骤停未遂、心源性猝死或合适的植入式心律转复除颤器[ICD]电击)的5年绝对风险,同时考虑个体风险因素及其随时间的变化。
基于罗切斯特的LQTS注册研究纳入了表型队列,该队列由1509名QTc≥470 ms的LQTS患者组成,以及基因型队列,其中包括1288名单一LQT1、LQT2或LQT3突变的患者。我们开发了两个独立的风险预测模型,其中包括预先指定的随时间变化的协变量,如β受体阻滞剂的使用情况、晕厥(从未晕厥、停用β受体阻滞剂时晕厥、使用β受体阻滞剂时晕厥)、年龄<13岁和≥13岁时的性别、基线QTc以及基因型(仅适用于基因型队列)。随访从登记入组开始,在患者50岁生日、因心源性猝死以外的原因死亡日期或最后一次联系时进行截尾,以先发生者为准。预测模型在来自意大利帕维亚的1481名LQTS患者的独立队列中进行了外部验证。
在罗切斯特数据集中,表型队列在中位随访9.0年期间有77个终点事件,基因型队列在中位随访9.8年期间有47个终点事件。在罗切斯特队列中,表型模型和基因型模型的Harrell广义C统计量的时间依赖性扩展分别为0.784(95%CI:0.740-0.827)和0.785(95%CI:0.721-0.849)。在帕维亚队列中通过外部验证获得的两个模型的C统计量分别为0.700(95%CI:0.610-0.790)和0.711(95%CI:0.631-0.792)。基于上述模型,开发了一个在线风险计算器,用于估计危及生命的心律失常事件的5年风险。
本研究分别为表型和基因型阳性的LQTS患者开发了两种风险预测算法。估计的5年绝对风险可用于量化LQTS患者发生危及生命的心律失常事件的风险,从而有助于关于预防性ICD治疗的临床决策。