Remotely Monitored Cardiac Implantable Electronic Device Data Predict All‐Cause and Cardiovascular Unplanned Hospitalization

Abstract

Background Unplanned hospitalizations are common in patients with cardiovascular disease. The “Triage Heart Failure Risk Status” (Triage‐HFRS) algorithm in patients with cardiac implantable electronic devices uses data from up to 9 device‐derived physiological parameters to stratify patients as low/medium/high risk of 30‐day heart failure (HF) hospitalization, but its use to predict all‐cause hospitalization has not been explored. We examined the association between Triage‐HFRS and risk of all‐cause, cardiovascular, or HF hospitalization. Methods and Results A prospective observational study of 435 adults (including patients with and without HF) with a Medtronic Triage‐HFRS–enabled cardiac implantable electronic device (cardiac resynchronization therapy device, implantable cardioverter‐defibrillator, or pacemaker). Cox proportional hazards models explored association between Triage‐HFRS and time to hospitalization; a frailty term at the patient level accounted for repeated measures. A total of 274 of 435 patients (63.0%) transmitted ≥1 high HFRS transmission before or during the study period. The remaining 161 patients never transmitted a high HFRS. A total of 153 (32.9%) patients had ≥1 unplanned hospitalization during the study period, totaling 356 nonelective hospitalizations. A high HFRS conferred a 37.3% sensitivity and an 86.2% specificity for 30‐day all‐cause hospitalization; and for HF hospitalizations, these numbers were 62.5% and 85.6%, respectively. Compared with a low Triage‐HFRS, a high HFRS conferred a 4.2 relative risk of 30‐day all‐cause hospitalization (8.5% versus 2.0%), a 5.0 relative risk of 30‐day cardiovascular hospitalization (3.6% versus 0.7%), and a 7.7 relative risk of 30‐day HF hospitalization (2.0% versus 0.3%). Conclusions In patients with cardiac implantable electronic devices, remotely monitored Triage‐HFRS data discriminated between patients at high and low risk of all‐cause hospitalization (cardiovascular or noncardiovascular) in real time.

Integration of a Smartphone HF-Dedicated App in the Remote Monitoring of Heart Failure Patients with Cardiac Implantable Electronic Devices: Patient Access, Acceptance, and Adherence to Use

“…Reduction in hospitalization, symptomatic improvement, and maximization of functional capacity represent the major challenges in heart failure management for the coming years. In HF patients with CIEDs, remote monitoring of implanted devices can help improve patient management through early diagnosis of heart failure events or risk stratification of cardiovascular and noncardiovascular adverse events [6,[9][10][11]. To improve the specificity of CIED remote monitoring and its ability to guide clinical decision making, an app was designed for a patient smartphone or tablet to receive information about clinical state of HF patients during follow-up.…”

“…By means of validated multiparametric analysis, CIEDs from different manufacturers can estimate the risk of developing AHF in the subsequent month, thus allowing physicians to act at a preclinical or subclinical stage. In particular, the HF risk score (HFRS) provided by the Medtronic TriageHF TM algorithm has been validated for AHF prediction on a large cohort of patients implanted with ICD or CRT-D devices [7][8][9] and has also been shown to predict all-cause and non-HF-related cardiovascular hospitalizations [9,10] as well as all-cause mortality [11].…”

Clinical Pathways Guided by Remotely Monitoring Cardiac Device Data: The Future of Device Heart Failure Management?

“…66 Recent real-world data from a Manchester, UK, cohort found that 60% of HF hospitalisations were preceded by a high-risk status within 30 days. 67 Beyond HF hospitalisation, recent studies have also examined the relationship between TriageHF status and all-cause mortality. One study examined data for 439 adults with TriageHF-compatible devices over a median 702-day follow-up.…”

“…There is increasing evidence from recent non-randomised and real-world studies indicating benefit. 47,67,69 Table 2 summarises HF RM platforms available in the UK.…”

Efficacy of the Cardiac Implantable Electronic Device Multisensory Triage-HF Algorithm in Heart Failure Care: A Real-World Clinical Experience

“…This stratification highlights other research findings focusing on “high-risk score” alerts, indicating that only the high-risk status is associated with an increased risk of HF hospitalization, designating high-risk alerts as actionable. However, previous studies on the triage-HF risk algorithm’s performance have reported wide variability in its sensitivity, specificity, and positive predictive values in predicting HF hospitalizations among high-risk scores [ 12 , 22 , 23 , 24 , 25 , 26 ]. Its sensitivity ranged from 31.5% to 98.6%, its specificity from 63.4% to 90.1%, and its positive predictive values from 4.1% to 55.9%.…”