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Safety and effectiveness of remote monitoring and prioritization of patients awaiting transcatheter aortic valve implantation: a propensity-matched prospective observational cohort study

Year: 2025

Type: article

Abstract: Aims Health systems face increasing waiting times for transcatheter aortic valve implantation (TAVI), incurring excess deaths and morbidity. To determine whether remote patient monitoring (RPM) using connected technologies can mitigate these risks by prioritizing patients awaiting TAVI, we aimed to measure the clinical safety and effectiveness of an RPM-based prioritization programme. Methods and results Prospective observational cohort study of all patients awaiting TAVI at Imperial College Healthcare NHS Trust, London, UK, between 24th April 2023 and 15th November 2023. An RPM pathway was implemented for all patients accepted for TAVI. These patients responded to a weekly symptom questionnaire via web, smartphone RPM platform or telephone monitoring; with rule-based clinical escalation. The primary endpoint was the rate of adverse events (defined as emergency department presentation, unplanned hospitalization, or death), compared with a propensity score-matched (PSM) historical control group. Secondary endpoints included pathway performance characteristics for detection of deterioration. 200 patients met inclusion criteria. Despite growth of the waiting list, responsible for longer waiting times experienced by the RPM group [median 104 days (IQR 61.00–176.00) vs. 75 days (IQR 38.75–118.00)], there was no difference in rates of adverse events between RPM-patients and historical controls (Log rank P = 0.9). The RPM pathway had high sensitivity for prediction of waiting list death (100%). Patients deemed at high-risk of deterioration experienced shorter waiting times to treatment. Conclusion RPM for patients awaiting TAVI is feasible and may mitigate the adverse effects of longer waiting times through accurate detection of deterioration and by informing prioritization decisions.

Source: European Heart Journal - Digital Health

DOI: 10.1093/ehjdh/ztaf114