mHealth-based management of heart failure during the early post-discharge period across frailty profiles: a post-hoc sub-analysis of the HERMeS multicentre randomised controlled trial
S Yun Viladomat, S Jovells-Vaque, A Herrero-Mateu, M Cobo Marcos, P Llacer Iborra, J M Garcia-Pinilla, A Gonzalez-Franco, J L Morales-Rull, J Nunez, E Garcia-Romero, L Onieva-Gil, A Eunice Cosa, E Olivera, C Enjuanes, J Comin-ColetAbstract
Background
Frailty is highly prevalent among patients with heart failure (HF) and is associated with an increased risk of adverse outcomes, particularly during the early post-discharge period. Despite this, frail patients are consistently underrepresented in HF eHealth and mHealth trials, which restricts both the evaluation and appropriate clinical indication of these solutions.
Purpose
To evaluate the effectiveness of incorporating mHealth-based non-invasive solutions combining telemonitoring and teleintervention into routine HF management during the vulnerable phase, with a specific focus on patients across different frailty profiles.
Methods
We conducted a post-hoc sub-analysis of the HERMeS clinical trial (NCT03663907). Frailty was assessed at baseline using a 65-item frailty index (FI) developed according to the Rockwood cumulative deficit approach, in which the FI is calculated as the ratio of deficits present to the total evaluated items. Based on established cut-offs from the literature, patients were stratified into three frailty categories: not frail (FI ≤ 0.210), more frail (FI 0.211–0.310), and most frail (FI ≥ 0.311). The primary outcome was a composite of worsening HF or cardiovascular (CV) death (first and recurrent).
Results
A total of 506 patients were included in the HERMeS clinical trial, with 255 allocated to the mHealth group and 251 to usual care. According to the FI, patients were distributed across frailty categories as follows: 132 (26%) were classified as not frail, 274 (54%) as more frail, and 100 (20%) as most frail. These patients were older (78 ± 9.07 years) and showed a more vulnerable clinical profile. During the 6-month follow-up, 35 most frail patients (35%) experienced the primary endpoint. Among them, 11 patients (61%) in the mHealth group reached the composite endpoint of worsening HF or CV death, compared with 24 patients (55%) in the usual care group (p=0.005). In this frailty subgroup, allocation to the mHealth intervention was associated with a significant reduction in the risk of the composite primary outcome (HR=0.34; 95% CI: 0.16–0.73; p=0.006). Overall, the beneficial effect of mHealth on the primary endpoint was consistent across frailty categories, with no significant interaction between treatment effect and frailty status (p for interaction >0.05) (Figures 1 and 2). Similar trends were observed for the individual components of the primary endpoint and for secondary clinical outcomes.
Conclusions
Incorporating mHealth-based solutions combining telemonitoring and teleintervention into routine HF management during the vulnerable phase appears to be effective regardless of patients’ frailty status. These findings support the integration of frailty assessment into clinical practice to guide, rather than limit, the use of digital health strategies, promoting their adaptation to patients’ real-world needs and avoiding the underuse of potentially beneficial interventions in frail HF patients.Number of events and hazard ratiosFor image description, please refer to the figure legend and surrounding text.Kaplan-Meier curveFor image description, please refer to the figure legend and surrounding text.