Baseline characteristics of patients enrolled in the AZIMUTH trial: an e-health-integrated, smartphone app-based, model of care for heart failure patients.

Abstract Aims The “FondAZione A. Gemelli IRCCS Artificial Intelligence Empowered Digital PlatforM to sUpport paTients with Heart Failure” (AZIMUTH) study is a multicenter prospective outpatient trial assessing an app-based, e-health-integrated model of care for heart failure (HF) patients. Its primary aim is to evaluate the feasibility and patient/provider acceptance of the app-based intervention, while key secondary aims include assessing its clinical impact through changes in guideline-directed medical therapy (GDMT) prescription/adherence and quality of life. Methods and Results Feasibility is defined as ≥70% of participants maintaining active engagement with the app during follow-up. The platform integrates patient-reported symptoms, connected measurements, medication reminders, and two-way messaging, with clinician review of alerts and trends. Between December 2021 and January 2024, 300 adults with chronic HF, irrespective of left ventricular ejection fraction (LVEF), were enrolled across four Italian centers. Median age was 66 years (IQR 59–73), 78.3% were male, and 82.3% were NYHA class I–II. LVEF distribution was balanced (HFrEF 35.3%, HFmrEF 25.7%, HFpEF 38.7%). Comorbidities were frequent: hypertension 81.3%, dyslipidemia 75.7%, ischemic heart disease 41.0%, diabetes 29.7%, atrial fibrillation 29.7%, and chronic kidney disease 21.7%. At enrollment, RASi/ARNI were prescribed in 69.6%, beta-blockers in 76.9%, MRAs in 16.1%, and SGLT2i in 23.7%. Compared with HFrEF-focused trials, uptake of foundational classes was lower, consistent with the broader LVEF spectrum and real-world constraints. Conclusion The AZIMUTH cohort represents a contemporary, heterogeneous HF population with variable and suboptimal GDMT uptake. Digital health interventions have the potential to optimize care delivery and increase adherence in real-world settings.

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Journal
European Heart Journal Open
Published
2026-04-30
DOI
https://doi.org/10.1093/ehjopen/oeag072
Primary Topic
Heart Failure Treatment and Management
Type
article
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article

Baseline characteristics of patients enrolled in the AZIMUTH trial: an e-health-integrated, smartphone app-based, model of care for heart failure patients.

Antonio Iaconelli, Attilio Restivo, Francesco Amico, Alice Luraschi et al.
European Heart Journal Open
Heart Failure Treatment and Management
article

Baseline characteristics of patients enrolled in the AZIMUTH trial: an e-health-integrated, smartphone app-based, model of care for heart failure patients.

Antonio Iaconelli, Attilio Restivo, Francesco Amico, Alice Luraschi, Donato Antonio Paglianiti, V. Bartoli, Enrico Incaminato, Konstantina Kostopoulou, Simona Giubilato, Francesco Canonico, Stefano Elia, Renzo Laborante, Agni Delvinioti, Stefano Patarnello, Thomas Griffiths, Federica Tomassini, Stefania Marcoli, Marco Gorini, Giuseppe Patti, Maurizio Volterrani, Gaetano Rizzo, Domenico D’Amario, Alfredo Cesario, Sofoklis Kyriazakos, Filippo Crea, Peter Fenici, Maria Catalano
article en

Abstract

Abstract Aims The “FondAZione A. Gemelli IRCCS Artificial Intelligence Empowered Digital PlatforM to sUpport paTients with Heart Failure” (AZIMUTH) study is a multicenter prospective outpatient trial assessing an app-based, e-health-integrated model of care for heart failure (HF) patients. Its primary aim is to evaluate the feasibility and patient/provider acceptance of the app-based intervention, while key secondary aims include assessing its clinical impact through changes in guideline-directed medical therapy (GDMT) prescription/adherence and quality of life. Methods and Results Feasibility is defined as ≥70% of participants maintaining active engagement with the app during follow-up. The platform integrates patient-reported symptoms, connected measurements, medication reminders, and two-way messaging, with clinician review of alerts and trends. Between December 2021 and January 2024, 300 adults with chronic HF, irrespective of left ventricular ejection fraction (LVEF), were enrolled across four Italian centers. Median age was 66 years (IQR 59–73), 78.3% were male, and 82.3% were NYHA class I–II. LVEF distribution was balanced (HFrEF 35.3%, HFmrEF 25.7%, HFpEF 38.7%). Comorbidities were frequent: hypertension 81.3%, dyslipidemia 75.7%, ischemic heart disease 41.0%, diabetes 29.7%, atrial fibrillation 29.7%, and chronic kidney disease 21.7%. At enrollment, RASi/ARNI were prescribed in 69.6%, beta-blockers in 76.9%, MRAs in 16.1%, and SGLT2i in 23.7%. Compared with HFrEF-focused trials, uptake of foundational classes was lower, consistent with the broader LVEF spectrum and real-world constraints. Conclusion The AZIMUTH cohort represents a contemporary, heterogeneous HF population with variable and suboptimal GDMT uptake. Digital health interventions have the potential to optimize care delivery and increase adherence in real-world settings.

European Heart Journal Open
Università Cattolica del Sacro Cuore (IT), Sprint (United States) (US), Università degli Studi del Piemonte Orientale “Amedeo Avogadro” (IT), Vita-Salute San Raffaele University (IT), Agostino Gemelli University Polyclinic (IT), Karolinska Institutet (SE), San Raffaele University of Rome (IT), Stockholm South General Hospital (SE), Ospedale San Giacomo Apostolo (IT), AstraZeneca (Singapore) (SG), Azienda Ospedaliero Universitaria Maggiore della Carita (IT), IRCCS Ospedale San Raffaele (IT), Ospedale Cannizzaro (IT), AstraZeneca (Italy) (IT), Ca' Foncello Hospital (IT), University of the Sacred Heart (JP), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Piedmont University (US)
Openalex Percentile: Top 10%
Heart Failure Treatment and Management
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