Survey to estimate the prevalence of type 2 diabetes mellitus in hospital patients in Germany by systematic HbA1c measurement upon admission

Int J Clin Pract. 2018 Dec;72(12):e13273. doi: 10.1111/ijcp.13273. Epub 2018 Oct 8.

Abstract

Objectives: The objective of this survey was to estimate the prevalence of type 2 diabetes mellitus (T2DM) in hospitalised patients ≥55 years based on routine HbA1c measurement upon admission, using the diagnosis algorithm according to the German National Diabetes Care Guideline.

Design: Non-interventional survey.

Setting: Four German maximum care hospitals.

Population: Consecutive patients ≥55 years of age admitted to hospital.

Main outcome measures: Participating hospitals measured HbA1c upon admission and applied the algorithm for diagnosing T2DM per the clinical recommendations of the American Diabetes Association (ADA) and the German National Diabetes Care Guideline as part of the clinical routine and allocated patients to three diagnostic categories: T2DM, increased risk for T2DM, no T2DM.

Results: Between Oct 2014 and May 2015, the survey documented data from 6092 patients; the analyses included 5820 patients fulfilling validity criteria (95.5%). Of these, 1906 (32.7%) had a known history of T2DM. Among the 3914 remaining patients, 2181 had no T2DM (55.8%), 1180 an increased risk for T2DM (30.1%) and 553 unrecognised T2DM (14.1%; 95% CI: 13.1%-15.3%). The overall prevalence of known and unrecognised T2DM was 42.3% (95% CI: 41.0%-43.5%). Patients with previously unrecognised T2DM were admitted to hospital predominantly for cardiac disorders (21.9%), nervous system disorders such as cerebral infarction (15.0%) and infections/infestations (13.4%).

Conclusions: This survey revealed an overall prevalence of known and unrecognised T2DM of more than 40%. Among patients with unrecognised T2DM on admission, the prevalence of T2DM was 14%. These data indicate that systematic documentation of T2DM in in-patients is clinically useful. Hospitals should consider using the diagnostic algorithm and to streamline pathways of care to secure adequate care considering patients' diabetic risk profiles, and to manage related additional costs.

Publication types

  • Observational Study

MeSH terms

  • Aged
  • Algorithms
  • Cross-Sectional Studies
  • Diabetes Mellitus, Type 2 / blood*
  • Diabetes Mellitus, Type 2 / diagnosis
  • Diabetes Mellitus, Type 2 / epidemiology*
  • Female
  • Germany / epidemiology
  • Glycated Hemoglobin / analysis*
  • Humans
  • Male
  • Middle Aged
  • Patient Admission
  • Prevalence
  • Surveys and Questionnaires

Substances

  • Glycated Hemoglobin A

Grants and funding