U.O. Electrophysiology, ASST Rhodense, 95 Viale Carlo Forlanini, 20024 Garbagnate Milanese (MI), Italy.
Cardiothoracovascular Department, Cattinara Hospital, ASUGI and University of Trieste, Trieste, Italy.
Europace. 2024 Feb 1;26(2). doi: 10.1093/europace/euae032.
To predict worsening heart failure hospitalizations (WHFHs) in patients with implantable defibrillators and remote monitoring, the HeartInsight algorithm (Biotronik, Berlin, Germany) calculates a heart failure (HF) score combining seven physiologic parameters: 24 h heart rate (HR), nocturnal HR, HR variability, atrial tachyarrhythmia, ventricular extrasystoles, patient activity, and thoracic impedance. We compared temporal trends of the HF score and its components 12 weeks before a WHFH with 12-week trends in patients without WHFH, to assess whether trends indicate deteriorating HF regardless of alert status.
Data from nine clinical trials were pooled, including 2050 patients with a defibrillator capable of atrial sensing, ejection fraction ≤ 35%, NYHA class II/III, no long-standing atrial fibrillation, and 369 WHFH from 259 patients. The mean HF score was higher in the WHFH group than in the no WHFH group (42.3 ± 26.1 vs. 30.7 ± 20.6, P < 0.001) already at the beginning of 12 weeks. The mean HF score further increased to 51.6 ± 26.8 until WHFH (+22% vs. no WHFH group, P = 0.003). As compared to the no WHFH group, the algorithm components either were already higher 12 weeks before WHFH (24 h HR, HR variability, thoracic impedance) or significantly increased until WHFH (nocturnal HR, atrial tachyarrhythmia, ventricular extrasystoles, patient activity).
The HF score was significantly higher at, and further increased during 12 weeks before WHFH, as compared to the no WHFH group, with seven components showing different behaviour and contribution. Temporal trends of HF score may serve as a quantitative estimate of HF condition and evolution prior to WHFH.
利用 HeartInsight 算法（德国柏林 Biotronik 公司）预测植入式除颤器和远程监测患者的心力衰竭恶化住院（WHFH），该算法通过结合 7 项生理参数计算心力衰竭（HF）评分：24 小时心率（HR）、夜间 HR、HR 变异性、房性心动过速/颤动、室性期前收缩、患者活动和胸腔阻抗。我们比较了 WHFH 前 12 周和无 WHFH 患者的 HF 评分及其各组成部分的时间趋势，以评估趋势是否表明 HF 恶化，而不论警报状态如何。
对九项临床试验的数据进行了汇总，共纳入 2050 例有除颤器且能感知心房、射血分数≤35%、纽约心脏协会（NYHA）心功能 II/III 级、无长期持续性房颤和 259 例患者中的 369 例 WHFH。WHFH 组的 HF 评分平均值高于无 WHFH 组（42.3±26.1 比 30.7±20.6，P<0.001），在 12 周开始时已经较高。HF 评分平均值进一步增加至 51.6±26.8，直至 WHFH（比无 WHFH 组增加 22%，P=0.003）。与无 WHFH 组相比，12 周前 WHFH 时算法组成部分已经较高（24 小时 HR、HR 变异性、胸腔阻抗）或直至 WHFH 时显著增加（夜间 HR、房性心动过速/颤动、室性期前收缩、患者活动）。
与无 WHFH 组相比，WHFH 前 12 周时 HF 评分显著升高，且在这 12 周内进一步升高，其中 7 个组成部分表现出不同的行为和贡献。HF 评分的时间趋势可以作为 WHFH 前 HF 状况和演变的定量估计。
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