Clinical validation of an artificial intelligence-based decision support system for diagnosis and risk stratification of heart failure (STRATIFYHF): a protocol for a prospective, multicentre longitudinal study

• Published in: BMJ open 2025-01, Vol.15 (1), p.e091793
• Main Authors: Charman, Sarah Jane, Okwose, Nduka C, Groenewegen, Amy, Del Franco, Annamaria, Tafelmeier, Maria, Preveden, Andrej, Garcia Sebastian, Cristina, Fuller, Amy S, Sinclair, David, Edwards, Duncan, Nelissen, Anne Pauline, Malitas, Petros, Zisaki, Aikaterini, Darba, Josep, Bosnic, Zoran, Vracar, Petar, Barlocco, Fausto, Fotiadis, Dimitris, Banerjee, Prithwish, MacGowan, Guy A, Fernandez, Oscar, Zamorano, José, Jiménez-Blanco Bravo, Marta, Maier, Lars S, Olivotto, Iacopo, Rutten, Frans H, Mant, Jonathan, Velicki, Lazar, Seferović, Petar M, Filipovic, Nenad, Jakovljevic, Djordje G, Fatima, Bano, Kate, Williams, Alessandra, Fornaro, Aleksandra, Milovancev, Meritxell, Ascanio, Ainoa, Aguera, Matej, Pičulin, Borut, Flis, Dimitrios, Boucharas, Dimitris, Manousos, Manolis, Tsiknakis, Thomas, Kassiotis, Tijana, Sustersic, Bogdan, Milicevic, Richard, Hobbs FD, Onno, Kaagman
• Format: Article
• Language: English
• Subjects: Aged; Artificial Intelligence; Blood tests; Cardiology; Cardiovascular Medicine; Clinical Decision-Making; Decision support systems; Decision Support Systems, Clinical; Disease; Ejection fraction; Female; Health sciences; Heart failure; Heart Failure - diagnosis; Hospitals; Humans; Longitudinal Studies; Male; Medical diagnosis; Medical personnel; Medical prognosis; Middle Aged; Mobile communications networks; Multicenter Studies as Topic; Observational Studies as Topic; Patients; Peptides; Primary care; Professional ethics; Prognosis; Prospective Studies; Protocol; Quality of life; Risk Assessment - methods; Risk management; Validation Studies as Topic
• ISSN: 2044-6055; 2044-6055
• DOI: 10.1136/bmjopen-2024-091793

IntroductionHeart failure (HF) is a complex clinical syndrome. Accurate risk stratification and early diagnosis of HF are challenging as its signs and symptoms are non-specific. We propose to address this global challenge by developing the STRATIFYHF artificial intelligence-driven decision support system (DSS), which uses novel analytical methods in determining the risk, diagnosis and prognosis of HF. The primary aim of the present study is to collect prospective clinical data to validate the STRATIFYHF DSS (in terms of diagnostic accuracy, sensitivity and specificity) as a tool to predict the risk, diagnosis and progression of HF. The secondary outcomes are the demographic and clinical predictors of risk, diagnosis and progression of HF.Methods and analysisSTRATIFYHF is a prospective, multicentre, longitudinal study that will recruit up to 1600 individuals (n=800 suspected/at risk of HF and n=800 diagnosed with HF) aged ≥45 years old, with up to 24 months of follow-up observations. Individuals suspected of HF will be divided into two categories based on current definitions and predefined inclusion criteria. All participants will have their medical history recorded, along with data on physical examination (signs and symptoms), blood tests including serum natriuretic peptides levels, ECG and echocardiogram results, as well as demographic, socioeconomic and lifestyle data, and use of complete novel technologies (cardiac output response to stress test and voice recognition biomarkers). All measurements will be recorded at baseline and at 12-month follow-up, with medical history and hospitalisation also recorded at 24-month follow-up. Cardiovascular MRI assessment will be completed in a subset of participants (n=20–40) from eligible clinical centres only at baseline. Each clinical centre will recruit a subset of participants (n=30) who will complete a 6-month home-based monitoring of clinical characteristics and accelerometry (wrist-worn monitor) to determine the feasibility and acceptability of the STRATIFYHF mobile application. Focus groups and semistructured interviews will be conducted with up to 15 healthcare professionals and up to 20 study participants (10 at risk of HF and 10 diagnosed with HF) to explore the needs of patients and healthcare professionals prior to the development of the STRATIFYHF DSS and to evaluate the acceptability of this mobile application.Ethics and disseminationEthical approval has been granted by the East Midlands - Leicester C