A systematic review of measures using clinical data for assessing the severity of Type 2 diabetes

Background/Aims: The assessment of disease severity in people with diabetes enables identification of patients in need for intensive and targeted therapies, and could help optimise the allocation of healthcare resources. We aimed to identify and appraise measures that have used clinical data to establish systems for grading Type 2 diabetes severity. Methods: MEDLINE, Embase and PubMed were searched between inception-June 2018. Data from studies on diabetes-specific severity grading measures derived by medical data in adult patients with Type 2 diabetes were extracted. Studies reporting only on other diabetes forms were excluded. Detailed characteristics of the eligible severity measures, including design, severity domains, and the association between severity and health-related outcomes, were identified following independent screening. Results: Eighteen severity measures in 17 papers including 32,314 participants were included. Measures’ designs were: diabetes severity index (N = 8 measures); severity categories (N = 7 measures); complications’ count (N = 2 measures); or severity checklist (N = 1 measure). The included domains differed greatly across the identified measures. Glucose or HbA1c levels and/or diabetes-related complications were included in 89% of the measures. Two severity measures were validated in a separate study population. Higher levels of diabetes severity were associated with poorer cognitive function, higher healthcare expenses, and significantly increased risks for hospitalisation and death. Conclusion: Increasing diabetes severity is associated with greater risks for adverse outcomes. Despite that our findings demonstrate the suitability of health records to assess diabetes severity, the clinical uptake of existing measures is poor. The need to advance diabetes severity assessment is important to develop actionable measures that would help benchmark efficient clinical services.