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Assessing the severity of Type 2 diabetes using clinical data-based measures: a systematic review.
Zghebi, S S; Panagioti, M; Rutter, M K; Ashcroft, D M; van Marwijk, H; Salisbury, C; Chew-Graham, C A; Buchan, I; Qureshi, N; Peek, N; Mallen, C; Mamas, M; Kontopantelis, E.
Afiliação
  • Zghebi SS; 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.
  • Panagioti M; NIHR School for Primary Care Research, Centre for Primary Care, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester.
  • Rutter MK; 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.
  • Ashcroft DM; NIHR School for Primary Care Research, Centre for Primary Care, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester.
  • van Marwijk H; Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester.
  • Salisbury C; Manchester Diabetes Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre (MAHSC), Manchester, Manchester.
  • Chew-Graham CA; NIHR School for Primary Care Research, Centre for Primary Care, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester.
  • Buchan I; Centre for Pharmacoepidemiology and Drug Safety, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester.
  • Qureshi N; Division of Primary Care and Public Health, Brighton and Sussex Medical School, University of Brighton, Brighton.
  • Peek N; Centre for Academic Primary Care, Department of Population Health Sciences, Bristol Medical School, Bristol.
  • Mallen C; Research Institute for Primary Care and Health Sciences, Keele University, Staffordshire.
  • Mamas M; 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.
  • Kontopantelis E; Health eResearch Centre, Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester.
Diabet Med ; 36(6): 688-701, 2019 06.
Article em En | MEDLINE | ID: mdl-30672017
ABSTRACT

AIMS:

To identify and critically appraise measures that use clinical data to grade the severity of Type 2 diabetes.

METHODS:

We searched MEDLINE, Embase and PubMed between inception and June 2018. Studies reporting on clinical data-based diabetes-specific severity measures in adults with Type 2 diabetes were included. We excluded studies conducted solely in participants with other types of diabetes. 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.

RESULTS:

We identified 6798 studies, of which 17 studies reporting 18 different severity measures (32 314 participants in 17 countries) were included a diabetes severity index (eight studies, 44%); severity categories (seven studies, 39%); complication count (two studies, 11%); and a severity checklist (one 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 hospitalization and mortality. The identified measures differed greatly in terms of the included domains. One study reported on the use of a severity measure prospectively.

CONCLUSIONS:

Health records are suitable for assessment of diabetes severity; however, the clinical uptake of existing measures is limited. The need to advance this research area is fundamental as higher levels of diabetes severity are associated with greater risks of adverse outcomes. Diabetes severity assessment could help identify people requiring targeted and intensive therapies and provide a major benchmark for efficient healthcare services.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Técnicas de Diagnóstico Endócrino / Regras de Decisão Clínica Tipo de estudo: Prognostic_studies / Systematic_reviews Limite: Adult / Humans Idioma: En Revista: Diabet Med Assunto da revista: ENDOCRINOLOGIA Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Técnicas de Diagnóstico Endócrino / Regras de Decisão Clínica Tipo de estudo: Prognostic_studies / Systematic_reviews Limite: Adult / Humans Idioma: En Revista: Diabet Med Assunto da revista: ENDOCRINOLOGIA Ano de publicação: 2019 Tipo de documento: Article