Remotely Monitored Cardiac Implantable Electronic Device Data Predicts All-Cause and Cardiovascular Unplanned Hospitalisation

Background
Unplanned hospitalisations are common in patients with cardiovascular disease. The ‘Triage Heart Failure Risk Status’ (Triage-HFRS) algorithm in patients with cardiac implantable electronic devices (CIEDs) uses data from up to 9 device-derived physiological parameters to stratify patients as low/medium/high-risk of 30-day heart failure-hospitalisation (HFH); but its use to predict all-cause hospitalisation in the has not been explored. We examined the association between Triage-HFRS and risk of all-cause-, cardiovascular-, or HF-hospitalisation (ACH, CVH, HFH).
Methods
A prospective observational study of 435 adults (including patients with and without HF) with a Medtronic Triage-HFRS enabled CIED (cardiac resynchronisation therapy ‘CRT’ device, implantable cardioverter-defibrillator ‘ICD’ or pacemaker). Cox proportional hazards models explored association between Triage-HFRS and time-to-hospitalisation; a frailty term at the patient-level accounted for repeated measures.
Results
274/435 patients (63.0%) transmitted >1 high HFRS transmission before or during the study period. The remaining 161 patients never transmitted a high HFRS. 153 (32.9%) patients had >1 unplanned hospitalisation during the study period totalling 356 non-elective hospitalisations. A high HFRS conferred a 37.3% sensitivity and 86.2% specificity for 30-day all-cause hospitalisation, and for heart failure hospitalisations, 62.5% and 85.6% respectively. Compared to a low Triage-HFRS, a high HFRS conferred a 4.2 relative risk of 30-day ACH (8.5% v 2.0%), 5.0 relative risk of 30-day CVH (3.6% v 0.7%), and 7.7 relative risk of 30-day HFH (2.0% v 0.3%).
Conclusion
In patients with CIEDs , remotely monitored Triage-HFRS data discriminated between patients at high and low risk of all-cause hospitalisation (cardiovascular or non-cardiovascular) in real-time.