Zghebi, SS, Mamas, MA ORCID: https://orcid.org/0000-0001-9241-8890, Ashcroft, DM, Salisbury, C, Mallen, CD ORCID: https://orcid.org/0000-0002-2677-1028, Chew-Graham, CA ORCID: https://orcid.org/0000-0002-9722-9981, Reeves, D, Van Marwijk, H, Qureshi, N, Weng, S, Holt, T, Buchan, I, Peek, N, Giles, S, Rutter, MK and Kontopantelis, E (2020) Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study. BMJ Open Diabetes Research and Care, 8 (1).

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Abstract

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.

Item Type: Article
Additional Information: This is the final published version (version of record). It was first published online via BMJ Publishing Group at http://dx.doi.org/10.1136/bmjdrc-2019-000962 - please refer to any applicable terms of use of the publisher.
Uncontrolled Keywords: diabetes, algorithms, electronic patient records, hospitalization, type 2 diabetes
Subjects: R Medicine > RC Internal medicine > RC660 Diabetes
Divisions: Faculty of Medicine and Health Sciences > School of Primary, Community and Social Care
Related URLs:
Depositing User: Symplectic
Date Deposited: 28 May 2020 10:59
Last Modified: 28 May 2020 11:02
URI: https://eprints.keele.ac.uk/id/eprint/8040

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