Academic Journal
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.
| العنوان: | 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. |
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| المؤلفون: | 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, STRATIFYHF investigators |
| بيانات النشر: | BMJ //doi.org/10.1136/bmjopen-2024-091793 BMJ Open |
| سنة النشر: | 2025 |
| المجموعة: | Apollo - University of Cambridge Repository |
| مصطلحات موضوعية: | Artificial Intelligence, Clinical Decision-Making, Heart failure, Risk management, Humans, Prospective Studies, Risk Assessment, Longitudinal Studies, Decision Support Systems, Clinical, Female, Middle Aged, Male, Aged, Multicenter Studies as Topic, Prognosis |
| الوصف: | Peer reviewed: True ; Publication status: Published ; INTRODUCTION: Heart 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 ANALYSIS: STRATIFYHF 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 ... |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | text/xml; application/pdf |
| اللغة: | English |
| Relation: | https://www.repository.cam.ac.uk/handle/1810/378317 |
| الاتاحة: | https://www.repository.cam.ac.uk/handle/1810/378317 |
| رقم الانضمام: | edsbas.2994572D |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |