| アブストラクト | OBJECTIVE: Clinically applicable diabetes severity measures are lacking, with no previous studies comparing their predictive value with glycated hemoglobin (HbA1c). We developed and validated a type 2 diabetes severity score (the DIabetes Severity SCOre, DISSCO) and evaluated its association with risks of hospitalization and mortality, assessing its additional risk information to sociodemographic factors and HbA1c. RESEARCH DESIGN AND METHODS: We used UK primary and secondary care data for 139 626 individuals with type 2 diabetes between 2007 and 2017, aged >/=35 years, and registered in general practices in England. The study cohort was randomly divided into a training cohort (n=111 748, 80%) to develop the severity tool and a validation cohort (n=27 878). We developed baseline and longitudinal severity scores using 34 diabetes-related domains. Cox regression models (adjusted for age, gender, ethnicity, deprivation, and HbA1c) were used for primary (all-cause mortality) and secondary (hospitalization due to any cause, diabetes, hypoglycemia, or cardiovascular disease or procedures) outcomes. Likelihood ratio (LR) tests were fitted to assess the significance of adding DISSCO to the sociodemographics and HbA1c models. RESULTS: A total of 139 626 patients registered in 400 general practices, aged 63+/-12 years were included, 45% of whom were women, 83% were White, and 18% were from deprived areas. The mean baseline severity score was 1.3+/-2.0. Overall, 27 362 (20%) people died and 99 951 (72%) had >/=1 hospitalization. In the training cohort, a one-unit increase in baseline DISSCO was associated with higher hazard of mortality (HR: 1.14, 95% CI 1.13 to 1.15, area under the receiver operating characteristics curve (AUROC)=0.76) and cardiovascular hospitalization (HR: 1.45, 95% CI 1.43 to 1.46, AUROC=0.73). The LR tests showed that adding DISSCO to sociodemographic variables significantly improved the predictive value of survival models, outperforming the added value of HbA1c for all outcomes. Findings were consistent in the validation cohort. CONCLUSIONS: Higher levels of DISSCO are associated with higher risks for hospital admissions and mortality. The new severity score had higher predictive value than the proxy used in clinical practice, HbA1c. This reproducible algorithm can help practitioners stratify clinical care of patients with type 2 diabetes. |
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| 投稿者 | Zghebi, Salwa S; Mamas, Mamas A; Ashcroft, Darren M; Salisbury, Chris; Mallen, Christian D; Chew-Graham, Carolyn A; Reeves, David; Van Marwijk, Harm; Qureshi, Nadeem; Weng, Stephen; Holt, Tim; Buchan, Iain; Peek, Niels; Giles, Sally; Rutter, Martin K; Kontopantelis, Evangelos |
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| 組織名 | NIHR School for Primary Care Research, Centre for Primary Care and Health;Services Research, Manchester Academic Health Science Centre (MAHSC), The;University of Manchester, Manchester, UK salwa.zghebi@manchester.ac.uk.;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), The University of Manchester, Manchester, UK.;Keele Cardiovascular Research Group, Centre for Prognosis Research, School of;Primary, Community and Social Care, Keele University, Stoke-on-Trent, UK.;University of Manchester, Manchester, UK.;Division of Pharmacy and Optometry, School of Health Sciences, Faculty of;Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC),;The University of Manchester, Manchester, UK.;NIHR Greater Manchester Patient Safety Translational Research Centre, The;NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science;Centre (MAHSC), Manchester, UK.;Centre for Academic Primary Care, Population Health Sciences, Bristol Medical;School, University of Bristol, Bristol, UK.;School of Primary, Community and Social Care, Faculty of Medicine and Health;Sciences, Keele University, Staffordshire, UK.;Centre for Biostatistics, School of Health Sciences, Faculty of Biology, Medicine;and Health, Manchester Academic Health Science Centre (MAHSC), The University of;Manchester, Manchester, UK.;Department of Primary Care and Public Health, Brighton and Sussex Medical School,;University of Sussex, Falmer, UK.;Primary Care Stratified Medicine (PRISM) Research Group, Division of Primary;Care, School of Medicine, University of Nottingham, Nottingham, UK.;Nuffield Department of Primary Care Health Sciences, University of Oxford,;Oxford, UK.;Institute of Population Health, University of Liverpool, Liverpool, UK.;Division of Informatics, Imaging and Data Sciences, School of Health Sciences,;Faculty of Biology, Medicine and Health, Manchester Academic Health Science;Centre (MAHSC), The University of Manchester, Manchester, UK.;Manchester Diabetes Centre, Manchester University NHS Foundation Trust,;Manchester Academic Health Science Centre (MAHSC), Manchester, UK.;Division of Diabetes, Endocrinology and Gastroenterology, School of Medical;Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health;Science Centre (MAHSC), The University of Manchester, Manchester, UK. |
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