| アブストラクト | AIMS: Heart failure (HF) is a growing problem in society with an ageing population and many patients with heart failure are affected by renal dysfunction. The RENAL-HF project aims to develop predictive risk models to support personalized renal function monitoring and treatment in patients with HF in primary care. METHODS AND RESULTS: This study will use electronic health records from the Clinical Practice Research Datalink (CPRD) database for patients who were diagnosed with HF. We will develop three prediction models-Mixed-effects model, Growth mixture model, and recurrent neural network-long short-term memory model to predict future worsening renal function, including events that lead to hospitalization, and death. Using an internal-external validation approach based on geographic region, we will choose the top-performing model using various metrics to evaluate the predictive performance. CONCLUSION: This protocol provides a detailed description of the methods used for developing and validating prognostic models for personalized renal function monitoring in people with HF in primary care. PROTOCOL REGISTRATION: The study and use of CPRD data were approved by the Independent Scientific Advisory Committee for Clinical Practice Research Datalink research (Protocol Number: 22_001794). |
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| 投稿者 | Vincent-Paulraj, Alexandar; Carr, Matthew J; Jenkins, David A; Muller-Myhsok, Bertram; Devonald, Mark; Wright, Jay; Williams, Nefyn; Peek, Niels; Pirmohamed, Munir; Ashcroft, Darren M |
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| 組織名 | Department of Pharmacology and Therapeutics, Institute of Systems Molecular and;Integrative Biology, University of Liverpool, Liverpool, UK.;Division of Pharmacy and Optometry, School of Health Sciences, Faculty of;Biology, Centre for Pharmacoepidemiology and Drug Safety, Medicine and Health,;University of Manchester, Manchester, UK.;NIHR Greater Manchester Patient Safety Research Collaboration, University of;Manchester, Manchester, UK.;Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine;and Health, University of Manchester, Manchester, UK.;Liverpool University Hospitals NHS Foundation Trust, University of Liverpool,;Liverpool, UK.;Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK.;Department of Primary Care and Mental Health, Institute of Population Health,;University of Liverpool, Liverpool, UK.;The Healthcare Improvement Studies Institute, Department of Public Health and;Primary Care, University of Cambridge, Cambridge, UK. |
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