Impact of High-Voltage Device Implantation in Elderly Japanese Patients With Heart Failure as Primary Prevention　- Post Hoc Analysis of HINODE.

BACKGROUND: Despite an increased incidence of chronic heart failure (HF) and sudden cardiac death (SCD), the use of implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy (CRT) is much lower in Japan than in Western countries. The HF Indication and SCD Prevention Trial Japan (HINODE) prospectively assessed the mortality rate, appropriately treated ventricular arrhythmias (VA), and HF in Japanese patients with a higher risk of HF.Methods and Results: HINODE consisted of ICD, CRT-defibrillator (CRT-D), pacing, and non-device treatment cohorts. This subanalysis evaluated the impact of the implantation of high-voltage devices (HVD; ICD and CRT-D) in 171 Japanese patients. We compared all-cause mortality, VA, and HF events between elderly (age >70 years at study enrollment) and non-elderly HVD recipients. The estimated survival rate through 24 months in the HVD cohort was 85.8% (97.5% lower control limit 77.6%). The risk of all-cause mortality was increased for the elderly vs. non-elderly (hazard ratio [HR] 2.82; 95% confidence interval [CI] 1.01-7.91; P=0.039), but did not differ after excluding ICD patients with CRT-D indication (HR 2.32; 95% CI 0.79-6.78; P=0.11). There were no differences in VA and HF event-free rates between elderly and non-elderly HVD recipients (P=0.73 and P=0.55, respectively). CONCLUSIONS: Although elderly patients may have a higher risk of mortality in general, the benefit of HVD therapy in this group is comparable to that in non-elderly patients.

Prediction of heart failure events based on physiologic sensor data in HINODE defibrillator patients.

AIMS: Hospitalizations are common in patients with heart failure and are associated with high mortality, readmission and economic burden. Detecting early signs of worsening heart failure may enable earlier intervention and reduce hospitalizations. The HeartLogic algorithm is designed to predict worsening heart failure using diagnostic data from multiple device sensors. The main objective of this analysis was to evaluate the sensitivity of the HeartLogic alert calculation in predicting worsening heart failure events (HFEs). We also evaluated the false positive alert rate (FPR) and compared the incidence of HFEs occurring in a HeartLogic alert state to those occurring out of an alert state. METHODS: The HINODE study enrolled 144 patients (81 ICD and 63 CRT-D) with device sensor data transmitted via a remote monitoring system. HeartLogic alerts were then retrospectively simulated using relevant sensor data. Clinicians and patients were blinded to calculated alerts. Reported adverse events with HF symptoms were adjudicated and classified by an independent HFE committee. Sensitivity was defined as the ratio of the number of detected usable HFEs (true positives) to the total number of usable HFEs. A false positive alert was defined as an alert with no usable HFE between the alert onset date and the alert recovery date plus 30 days. The patient follow-up period was categorized as in alert state or out of alert state. The event rate ratio was the HFE rate calculated in alert to out of alert. RESULTS: The patient cohort was 79% male and had an average age of 68 ± 12 years. This analysis yielded 244 years of follow-up data with 73 HFEs from 37 patients. A total of 311 HeartLogic alerts at the nominal threshold (16) occurred across 106 patients providing an alert rate of 1.27 alerts per patient-year. The HFE rate was 8.4 times greater while in alert compared with out of alert (1.09 vs. 0.13 events per patient-year; P < 0.001). At the nominal alert threshold, 80.8% of HFEs were detected by a HeartLogic alert [95% confidence interval (CI): 69.9%-89.1%]. The median time from first true positive alert to an adjudicated clinical HFE was 53 days. The FPR was 1.16 (95% CI: 0.98-1.38) alerts per patient-year. CONCLUSIONS: Results suggest that signs of worsening HF can be detected successfully with remote patient follow-up. The use of HeartLogic may predict periods of increased risk for HF or clinically significant events, allowing for early intervention and reduction of hospitalization in a vulnerable patient population.