| アブストラクト | INTRODUCTION: The increasing prevalence of type 2 diabetes mellitus (T2DM) presents a significant burden on affected individuals and healthcare systems internationally. There is, however, no agreed validated measure to infer diabetes severity from electronic health records (EHRs). We aim to quantify T2DM severity and validate it using clinical adverse outcomes. METHODS AND ANALYSIS: Primary care data from the Clinical Practice Research Datalink, linked hospitalisation and mortality records between April 2007 and March 2017 for patients with T2DM in England will be used to develop a clinical algorithm to grade T2DM severity. The EHR-based algorithm will incorporate main risk factors (severity domains) for adverse outcomes to stratify T2DM cohorts by baseline and longitudinal severity scores. Provisionally, T2DM severity domains, identified through a systematic review and expert opinion, are: diabetes duration, glycated haemoglobin, microvascular complications, comorbidities and coprescribed treatments. Severity scores will be developed by two approaches: (1) calculating a count score of severity domains; (2) through hierarchical stratification of complications. Regression models estimates will be used to calculate domains weights. Survival analyses for the association between weighted severity scores and future outcomes-cardiovascular events, hospitalisation (diabetes-related, cardiovascular) and mortality (diabetes-related, cardiovascular, all-cause mortality)-will be performed as statistical validation. The proposed EHR-based approach will quantify the T2DM severity for primary care performance management and inform the methodology for measuring severity of other primary care-managed chronic conditions. We anticipate that the developed algorithm will be a practical tool for practitioners, aid clinical management decision-making, inform stratified medicine, support future clinical trials and contribute to more effective service planning and policy-making. ETHICS AND DISSEMINATION: The study protocol was approved by the Independent Scientific Advisory Committee. Some data were presented at the National Institute for Health Research School for Primary Care Research Showcase, September 2017, Oxford, UK and the Diabetes UK Professional Conference March 2018, London, UK. The study findings will be disseminated in relevant academic conferences and peer-reviewed journals. |
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| 投稿者 | Zghebi, Salwa S; Rutter, Martin K; Ashcroft, Darren M; Salisbury, Chris; Mallen, Christian; Chew-Graham, Carolyn A; Reeves, David; van Marwijk, Harm; Qureshi, Nadeem; Weng, Stephen; Peek, Niels; Planner, Claire; Nowakowska, Magdalena; Mamas, Mamas; Kontopantelis, Evangelos |
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| 組織名 | Division of Population Health, Health Services Research and Primary Care, School;of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic;Health Science Centre (MAHSC), University of Manchester, Manchester, UK.;NIHR School for Primary Care Research, Centre for Primary Care, Manchester;Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.;Division of Diabetes, Endocrinology and Gastroenterology, School of Medical;Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health;Science Centre (MAHSC), University of Manchester, Manchester, UK.;Manchester Diabetes Centre, Manchester University NHS Foundation Trust,;Manchester Academic Health Science Centre (MAHSC), Manchester, UK.;Division of Pharmacy and Optometry, School of Health Sciences, Faculty of;Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC),;University of Manchester, Manchester, UK.;Centre for Academic Primary Care, Population Health Sciences, Bristol Medical;School, University of Bristol, Bristol, UK.;Research Institute for Primary Care and Health Sciences, Keele University,;Staffordshire, UK.;Division of Primary Care and Public Health, Brighton and Sussex Medical School,;University of Brighton, Brighton, UK.;Division of Primary Care, School of Medicine, University of Nottingham,;Nottingham, UK.;Division of Informatics, Imaging & Data Sciences (L5), School of Health Sciences,;Faculty of Biology, Medicine and Health, Manchester Academic Health Science;Centre (MAHSC), University of Manchester, Manchester, UK.;Keele Cardiovascular Research group, Centre for Prognosis Research, Institute for;Primary Care and Health Sciences, Keele University, Stoke-on-Trent, UK. |
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