Cardoso Isabel, Cunha Pedro Silva, Laranjo Sérgio, Grazina André, Viegas José Miguel, Portugal Guilherme, Valente Bruno, Lousinha Ana, Brás Pedro, Brás Manuel, Ferreira Rui C, Oliveira Mário
Cardiology Service, Central Lisbon Hospital and University Centre, Lisbon, Portugal.
Arrhythmology, Pacing, and Electrophysiology Unit, Cardiology Service, Central Lisbon Hospital and University Centre, Lisbon, Portugal.
J Innov Card Rhythm Manag. 2023 Sep 15;14(9):5576-5581. doi: 10.19102/icrm.2023.14093. eCollection 2023 Sep.
The heart failure risk status (HFRS) is a validated dynamic tool for risk score prediction, based on the TriageHF™ algorithm (Medtronic, Minneapolis, MN, USA), for the occurrence of a heart failure (HF) event in the 30 days following a remote monitoring (RM) transmission. The aim of this study was to evaluate the accuracy of the HFRS in predicting an unplanned hospital admission due to HF decompensation in a real-world cohort of patients submitted to cardiac resynchronization therapy (CRT). We conducted a single-center review of a cohort of 40 consecutive HF patients, under RM, with CRT devices using the HFRS of the TriageHF™ algorithm. The correlation of the HFRS with hospital admissions was analyzed. During a mean follow-up of 36 months, a stepwise increase in the HFRS was significantly associated with a higher risk of HF admission (odds ratio, 12.7; 95% confidence interval, 3.2-51.5; < .001), and the HFRS was demonstrated to have good discrimination for HF hospitalization, with an area under the receiver-operating characteristic curve of 0.812. The TriageHF™ algorithm effectively predicted HF-related hospitalization in a cohort of CRT patients during long-term RM follow-up, providing a novel clinical pathway to optimize the clinical management of this complex population.
心力衰竭风险状态(HFRS)是一种经过验证的动态风险评分预测工具,基于TriageHF™算法(美敦力公司,美国明尼阿波利斯),用于预测远程监测(RM)传输后30天内心力衰竭(HF)事件的发生。本研究的目的是评估HFRS在预测接受心脏再同步治疗(CRT)的真实世界患者队列中因HF失代偿导致的非计划住院方面的准确性。我们对连续40例接受RM且使用TriageHF™算法的HFRS的CRT设备的HF患者队列进行了单中心回顾。分析了HFRS与住院情况的相关性。在平均36个月的随访期间,HFRS的逐步增加与HF住院风险较高显著相关(优势比,12.7;95%置信区间,3.2 - 51.5;P <.001),并且HFRS被证明对HF住院具有良好的辨别能力,受试者操作特征曲线下面积为0.812。TriageHF™算法在长期RM随访期间有效预测了CRT患者队列中与HF相关的住院情况,为优化这一复杂人群的临床管理提供了一种新的临床途径。