Efficacy of remote home telemonitoring (HTM) on congestion control and heart failure (HF) hospitalizations in HF out-patients

Abstract

Abstract Introduction Heart failure (HF) burden is characterized by high hospitalizations rates, impairing patients survival and quality of life. Yet, early detection and control of congestion with home tele-monitoring (HTM) might help to reduce HF hospitalizations (HFH) (1). Aim To report our experience of congestion management with HTM for HF patients in out-hospital setting. Methods All HF patients followed with the HTM program of our HF clinic between July 2020 and December 2022 were included. For each patient, HTM consisted in daily body weight and symptoms tele-transmission through a connected device. History of HFH were recorded 18 months before and up to 18 months after inclusion in HTM. Alerts were defined as weight gain (WA) (≥ 3 kgs in 2 days or ≥ 2 kgs in 5 days) and/or new symptoms (SA) onset (≥ 3 in 1 day or identical 3 times in 4 days). Relevants HTM alerts were transmitted by the service provider to the local HF team to be managed within 48 hours : phone contact and/or NT-proBNP dosing and/or physical consultation and/or treatment adaptation. Results Among the 147 patients included, mean age was 60±12 years, 110 (75%) were males. Mean left ventricle ejection fraction (LVEF) was 34±11%, and 112 (76%) had HF-rEF, 19 (13%) HF-mrEF and 16 (11%) HF-pEF. Other baselines characteristics are resumed in Table1. Mean HTM duration was 391±250 days and mean device observance was 74±21%. During HTM, 85 (59%) alerts were managed by the HF team in a mean delay of 98±114 days after inclusion : 47 (32%) WA, 34 (23%) SA and 4 (3%) W+SA. After Student-paired test compared to D0 (day of alert transmission), mean weight (kgs) at D2, D5, D10, D21 and D30 were significantly lower (all p<10E-3), respectively 91±17 versus 90±17, 89±17, 89±16, 88±16 and 89±17 kgs (Fig.1A). After Wilcoxon paired-test, the same difference was observed for symptoms (all p<10E-3) : 3±2 (D0) versus 1±1 (D2), 0.7±1 (D5), 0.4±0.8 (D10), 0.5±0.7 (D21) and 0.5±0.9 (D30) (Fig.1B). Patients HFH rates were significantly lower after HTM inclusion : 19 HFH (13%) after HTM versus 70 (48%) before, according to McNemar's X2 test (p<10E-11) (Fig.1C). Notably, post-HTM observed HFH rates (13%) also differed significantly from the 20% expected in a general HF population (2). For the 15 patients (10%) with history of HFH both before and after HTM implementation, mean lengths of stay (LOS) were significantly lower when HFH occurs after HTM inclusion according to Wilcoxon signed rank test : 10±12 vs 22±19 days (-12±17 days, p=0.02) (Fig.1D). Conclusion In our experience, HTM is a efficient to help controling congestion and symptoms of HF patients in out-hospital setting, and can help to reduce HFH, providing that each alerts is being timely and appropriately addressed by the HF team. Prospective studies are needed to confirm these results.Impact of HTM on congestion and HFHTable 1.Patients characteristics.