Clinica di Cardiologia e Aritmologia, Università Politecnica delle Marche, "Ospedali Riuniti", Via Conca, 71, 60020, Ancona, Italy.
"Giovan Battista Grassi" Hospital, Rome, Italy.
ESC Heart Fail. 2019 Apr;6(2):308-318. doi: 10.1002/ehf2.12394. Epub 2019 Jan 11.
In the Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients study, a novel algorithm for heart failure (HF) monitoring was implemented. The HeartLogic (Boston Scientific) index combines data from multiple implantable cardioverter defibrillator (ICD)-based sensors and has proved to be a sensitive and timely predictor of impending HF decompensation. The remote monitoring of HF patients by means of HeartLogic has never been described in clinical practice. We report post-implantation data collected from sensors, the combined index, and their association with clinical events during follow-up in a group of patients who received a HeartLogic-enabled device in clinical practice.
Patients with ICD and cardiac resynchronization therapy ICD were remotely monitored. In December 2017, the HeartLogic feature was activated on the remote monitoring platform, and multiple ICD-based sensor data collected since device implantation were made available: HeartLogic index, heart rate, heart sounds, thoracic impedance, respiration, and activity. Their association with clinical events was retrospectively analysed. Data from 58 patients were analysed. During a mean follow-up of 5 ± 3 months, the HeartLogic index crossed the threshold value (set by default to 16) 24 times (over 24 person-years, 0.99 alerts/patient-year) in 16 patients. HeartLogic alerts preceded five HF hospitalizations and five unplanned in-office visits for HF. Symptoms or signs of HF were also reported at the time of five scheduled visits. The median early warning time and the time spent in alert were longer in the case of hospitalizations than in the case of minor events of clinical deterioration of HF. HeartLogic contributing sensors detected changes in heart sound amplitude (increased third sound and decreased first sound) in all cases of alerts. Patients with HeartLogic alerts during the observation period had higher New York Heart Association class (P = 0.025) and lower ejection fraction (P = 0.016) at the time of activation.
Our retrospective analysis indicates that the HeartLogic algorithm might be useful to detect gradual worsening of HF and to stratify risk of HF decompensation.
在多传感器慢性评估门诊心力衰竭患者研究中，实施了一种用于心力衰竭（HF）监测的新算法。HeartLogic（波士顿科学公司）指数结合了来自多个植入式心脏复律除颤器（ICD）的传感器数据，已被证明是心力衰竭失代偿即将发生的敏感且及时的预测指标。通过 HeartLogic 对 HF 患者进行远程监测在临床实践中从未被描述过。我们报告了一组在临床实践中接受启用 HeartLogic 设备的患者在随访期间从传感器收集的植入后数据、联合指数及其与临床事件的关联。
对 ICD 和心脏再同步治疗 ICD 患者进行了远程监测。2017 年 12 月，HeartLogic 功能在远程监测平台上激活，自设备植入以来收集的多个基于 ICD 的传感器数据可用：HeartLogic 指数、心率、心音、胸阻抗、呼吸和活动。回顾性分析它们与临床事件的关联。分析了 58 例患者的数据。在平均 5±3 个月的随访期间，16 例患者的 HeartLogic 指数（默认设置为 16）超过阈值 24 次（24 人年，0.99 次警报/患者年）。HeartLogic 警报先于 5 次 HF 住院和 5 次非计划 HF 门诊就诊。在 5 次预定就诊时也报告了 HF 的症状或体征。在因 HF 恶化的住院治疗情况下，早期预警时间和警报持续时间比因 HF 恶化的较小事件的情况下更长。在所有警报的情况下，HeartLogic 贡献的传感器均检测到心音幅度的变化（第三心音增加和第一心音降低）。在观察期间有 HeartLogic 警报的患者在激活时具有更高的纽约心脏协会（NYHA）心功能分级（P=0.025）和更低的射血分数（P=0.016）。
我们的回顾性分析表明，HeartLogic 算法可能有助于检测 HF 的逐渐恶化并分层 HF 失代偿的风险。
