Executive Board, Leiden University Medical Centre, Leiden, the Netherlands.
Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands.
Int J Cardiol. 2024 Nov 15;415:132421. doi: 10.1016/j.ijcard.2024.132421. Epub 2024 Aug 3.
BACKGROUND & AIMS: Early identification of worsening HF enables timely adjustments to prevent hospitalization. Recent studies show the HeartLogic™ algorithm detects congestion and reduces HF events. However, it is unclear which patients benefit most. Therefore, this study aims to identify and characterize HF patients who benefit most from CIED-based remote monitoring with HeartLogic™.
In this multicenter retrospective study, patients with a CIED and HeartLogic™ algorithm under structured follow-up were included. Patients were classified as having "substantial benefit" or "no benefit" from monitoring.
In total, 242 patients were included (male n = 190, 79%, median age 61 years [IQR 61-77]). Median follow-up was 1.2 years [IQR 1.1-2.7]. Among 378 alerts, 266 were true positive (70%) and 112 false positive (30%). Of the 242 patients, 69 (29%) were classified as having "substantial benefit", while 173 (71%) had "no benefit" from HeartLogic™ monitoring. Univariate and multivariate analysis showed that patients with "substantial benefit" had higher NYHA functional class (OR 2.64, P = 0.004), higher NT-ProBNP (OR 1.02, P = 0.003), higher serum creatinine (OR 1.10, P < 0.001), lower LVEF (OR 1.19, P = 0.004), more severe mitral regurgitation (OR 2.16, P = 0.006), higher right ventricular end diastolic volume (OR 1.05, P = 0.040), higher pulmonary artery pressures (OR 1.19, P = 0.003), and were more likely to use loop diuretics (OR 2.79, P = 0.001). Among patients with "substantial benefit," the positive predictive value (PPV) of HeartLogic™ to detect congestion was 92%.
The utilization of CIED-based HeartLogic™ driven HF care demonstrated pronounced efficacy, predominantly in patients exhibiting characteristics of HF at a more advanced disease stage.
早期识别 HF 恶化情况有助于及时调整以预防住院。最近的研究表明，HeartLogic™算法可检测充血并减少 HF 事件。然而，尚不清楚哪些患者受益最大。因此，本研究旨在确定并描述从基于 CIED 的远程监测 HeartLogic™中获益最大的 HF 患者。
在这项多中心回顾性研究中，纳入了接受 CIED 和 HeartLogic™算法进行结构化随访的患者。将患者分为监测有“明显获益”或“无获益”。
共纳入 242 例患者（男性 n=190，79%，中位年龄 61 岁[IQR 61-77]）。中位随访时间为 1.2 年[IQR 1.1-2.7]。在 378 次警报中，266 次为真阳性（70%），112 次为假阳性（30%）。在 242 例患者中，69 例（29%）被归类为有“明显获益”，而 173 例（71%）从 HeartLogic™监测中“无获益”。单变量和多变量分析表明，有“明显获益”的患者 NYHA 心功能分级更高（OR 2.64，P=0.004），NT-ProBNP 更高（OR 1.02，P=0.003），血清肌酐更高（OR 1.10，P<0.001），LVEF 更低（OR 1.19，P=0.004），二尖瓣反流更严重（OR 2.16，P=0.006），右心室舒张末期容积更高（OR 1.05，P=0.040），肺动脉压更高（OR 1.19，P=0.003），更有可能使用袢利尿剂（OR 2.79，P=0.001）。在有“明显获益”的患者中，HeartLogic™检测充血的阳性预测值（PPV）为 92%。
基于 CIED 的 HeartLogic™驱动的 HF 治疗显示出显著疗效，主要在处于更晚期疾病阶段的 HF 表现出特征的患者中。
