Unità Operativa di Elettrofisiologia, Studio e Terapia delle Aritmie", Monaldi Hospital, Naples, Italy.
OO.RR. San Giovanni di Dio Ruggi d'Aragona, Salerno, Italy.
Heart Rhythm. 2023 Jul;20(7):992-997. doi: 10.1016/j.hrthm.2023.03.026. Epub 2023 Mar 24.
The HeartLogic algorithm (Boston Scientific) has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation.
The purpose of this study was to determine whether remotely monitored data from this algorithm could be used to identify patients at high risk for mortality.
The algorithm combines implantable cardioverter-defibrillator (ICD)-measured accelerometer-based heart sounds, intrathoracic impedance, respiration rate, ratio of respiration rate to tidal volume, night heart rate, and patient activity into a single index. An alert is issued when the index crosses a programmable threshold. The feature was activated in 568 ICD patients from 26 centers.
During median follow-up of 26 months [25th-75th percentile 16-37], 1200 alerts were recorded in 370 patients (65%). Overall, the time IN-alert state was 13% of the total observation period (151/1159 years) and 20% of the follow-up period of the 370 patients with alerts. During follow-up, 55 patients died (46 in the group with alerts). The rate of death was 0.25 per patient-year (95% confidence interval [CI] 0.17-0.34) IN-alert state and 0.02 per patient-year (95% CI 0.01-0.03) OUT of the alert state, with an incidence rate ratio of 13.72 (95% CI 7.62-25.60; P <.001). After multivariate correction for baseline confounders (age, ischemic cardiomyopathy, kidney disease, atrial fibrillation), the IN-alert state remained significantly associated with the occurrence of death (hazard ratio 9.18; 95% CI 5.27-15.99; P <.001).
The HeartLogic algorithm provides an index that can be used to identify patients at higher risk for all-cause mortality. The index state identifies periods of significantly increased risk of death.
HeartLogic 算法（波士顿科学公司）已被证明是预测心力衰竭（HF）失代偿的一种敏感且及时的预测指标。
本研究旨在确定该算法的远程监测数据是否可用于识别高死亡率风险的患者。
该算法将植入式心脏复律除颤器（ICD）测量的加速度计心脏音、胸腔内阻抗、呼吸率、呼吸率与潮气量比、夜间心率和患者活动结合成一个单一的指标。当指数超过可编程阈值时，就会发出警报。该功能在 26 个中心的 568 例 ICD 患者中激活。
在中位随访 26 个月[25 至 75 百分位 16 至 37]期间，370 例患者（65%）中有 1200 次警报记录。总体而言，处于警报状态的时间占总观察期的 13%（151/1159 年），占有警报的 370 例患者随访期的 20%。随访期间，55 例患者死亡（有警报的患者中 46 例）。在警报状态下，死亡发生率为 0.25 例/患者-年（95%置信区间[CI] 0.17-0.34），在警报状态外，死亡发生率为 0.02 例/患者-年（95%CI 0.01-0.03），发病率比为 13.72（95%CI 7.62-25.60；P<.001）。对年龄、缺血性心肌病、肾脏疾病、心房颤动等基线混杂因素进行多变量校正后，处于警报状态与死亡的发生仍显著相关（危险比 9.18；95%CI 5.27-15.99；P<.001）。
HeartLogic 算法提供了一个可用于识别全因死亡率较高的患者的指数。该指数状态确定了死亡风险显著增加的时期。
