Assessing the Severity of Type 2 Diabetes Using Clinical Data Derived Metrics: a Systematic Review

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To identify and critically-appraise metrics using clinical data to grade the severity of type 2 diabetes.
We searched MEDLINE, Embase and PubMed between inception-June 2018. Studies reporting on clinical data-derived, diabetes-specific severity metrics in adults with type 2 diabetes were included. We excluded studies solely reporting other diabetes forms. After independent screening, the characteristics of the eligible measures including design and severity domains, the clinical utility of developed measures, and the relationship between severity levels and health-related outcomes were assessed.
We identified 6,798 papers, from which 17 studies reporting 18 severity measures (32,314 participants, 17 countries) were included: diabetes severity index (8 studies, 44%); severity categories (7 studies, 39%); complication count (2 studies,11%); or severity checklist (1 study, 6%). Nearly 89% of the measures included diabetes-related complications and/or glycaemic control indicators. Two of the severity measures were validated in a separate study population. More severe diabetes was associated with increased healthcare costs, poorer cognitive function, and significantly greater risks of hospitalisation and mortality. The identified metrics differed greatly in terms of the included domains. One study reported on the use of a severity measure prospectively.
Electronic health record data can be reused to better assess diabetes severity. However, the clinical uptake of existing metrics is limited. The need to advance such metrics is important for averting the poorer outcomes that patients with more severe diabetes experience. Diabetes severity assessment could help identify people requiring targeted and intensive therapies and provide a major benchmark for efficient healthcare services.

Bibliographical metadata

Original languageEnglish
JournalDiabetic Medicine
Early online date22 Jan 2019
Publication statusPublished - 2019