Heart failure (HF) is a global pandemic and accounts for substantial morbidity and healthcare expenditure, largely due to frequent hospitalizations. While traditionally HF patients are followed with intermittent clinical assessments, wearable technologies offer continuous, real-time monitoring, potentially enabling earlier detection and tailored interventions to prevent hospitalization. This systematic review evaluates the impact of noninvasive wearable devices on hospitalizations in HF. Following PRISMA guidelines, literature searches were conducted in PubMed and Scopus using keywords related to HF, hospitalization, and wearable technology on 1 March 2024, and re-run on 3 December 2024. Studies assessing the link between wearable devices and HF-related hospitalization rates were included. Data extraction covered population characteristics, study design, type of device, and hospitalization rates. Risk of bias was assessed using ROBINS-I and ROB-2 tools. Meta-analysis was attempted but not performed due to significant heterogeneity (I2>90%). From 2247 records, eight studies involving 1823 patients were finally analysed. Devices included ReDS, VitalPatch, ZOLL LifeVest, and ZOLL-HFMS, with follow-up ranging from 30 to 646 days. Wearable devices allowed prediction of HF hospitalization within 6.5–32 days in advance. Wearable-guided therapy compared to traditional assessment showed an 89% relative reduction at 30 days in a single-blind randomized-controlled trial, and 78% and 87% reductions in 30-day and 90-day hospitalization rates in observational studies. Although these data highlight the potential of wearable devices in HF management, future research should test predefined wearable-guided treatment algorithms on strong endpoints and address cost-effectiveness and data security in large randomized-controlled trials with longer follow-up.

Wearable technologies to predict and prevent and heart failure hospitalizations: a systematic review

Noci, Francesca
Primo
;
Capodici, Angelo
Secondo
;
Nuti, Sabina;Passino, Claudio;Emdin, Michele;Giannoni, Alberto
2025-01-01

Abstract

Heart failure (HF) is a global pandemic and accounts for substantial morbidity and healthcare expenditure, largely due to frequent hospitalizations. While traditionally HF patients are followed with intermittent clinical assessments, wearable technologies offer continuous, real-time monitoring, potentially enabling earlier detection and tailored interventions to prevent hospitalization. This systematic review evaluates the impact of noninvasive wearable devices on hospitalizations in HF. Following PRISMA guidelines, literature searches were conducted in PubMed and Scopus using keywords related to HF, hospitalization, and wearable technology on 1 March 2024, and re-run on 3 December 2024. Studies assessing the link between wearable devices and HF-related hospitalization rates were included. Data extraction covered population characteristics, study design, type of device, and hospitalization rates. Risk of bias was assessed using ROBINS-I and ROB-2 tools. Meta-analysis was attempted but not performed due to significant heterogeneity (I2>90%). From 2247 records, eight studies involving 1823 patients were finally analysed. Devices included ReDS, VitalPatch, ZOLL LifeVest, and ZOLL-HFMS, with follow-up ranging from 30 to 646 days. Wearable devices allowed prediction of HF hospitalization within 6.5–32 days in advance. Wearable-guided therapy compared to traditional assessment showed an 89% relative reduction at 30 days in a single-blind randomized-controlled trial, and 78% and 87% reductions in 30-day and 90-day hospitalization rates in observational studies. Although these data highlight the potential of wearable devices in HF management, future research should test predefined wearable-guided treatment algorithms on strong endpoints and address cost-effectiveness and data security in large randomized-controlled trials with longer follow-up.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/581532
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