4.5 Article

Characteristics of different risk factors and fasting plasma glucose for identifying GDM when using IADPSG criteria: a cross-sectional study

Journal

BMC PREGNANCY AND CHILDBIRTH
Volume 18, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/s12884-018-1875-1

Keywords

Gestational diabetes mellitus; Screening; Fasting plasma glucose; Risk factors; Sensitivity

Funding

  1. Research committee of Orebro County

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Background: The Swedish National Board of Health and Welfare (SNBHW) recommended the new diagnostic criteria for GDM based upon Hyperglycaemia and Adverse Pregnancy Outcomes (HAPO) study thresholds. Due to limited knowledge base, no recommendations were made on GDM screening. The aim of this study is to evaluate test characteristics of risk factors and fasting blood glucose as screening tests for diagnosing GDM using diagnostic thresholds based upon HAPO study 1.75/2.0 (model I/II respectively) odds ratio for adverse pregnancy outcomes. Methods: This cross-sectional, population-based study included all pregnant women who attended maternal health care in Orebro County, Sweden between the years 1994-96. A 75 g OGTT with capillary fasting and 2-h blood glucose was offered to all pregnant women at week 28-32. Risk factors and repeated random glucose samples were collected. Sensitivity, specificity and predictive values of blood glucose were calculated. Results: Prevalence of GDM was 11.7% with model I and 7.2% with the model II criteria. Risk factors showed 28%, (95% CI 24-32) and 31%, (95% CI 25-37) sensitivity for model I and II respectively. A fasting cut off >= 4.8 mmol/l occurred in 24% of women with 91%, (95% CI 88-94) sensitivity and 85%, (95% CI 83-86) specificity using model I while a fasting cut off >= 5.0 mmol/l occurred in 14% with 91%, (95% CI 87-94) sensitivity and 92%, (95% CI 91-93) specificity using model II. Conclusion: Risk factor screening for GDM was found to be poorly predictive of GDM but fasting glucose of 4.8-5. 0 mmol/l showed good test characteristics irrespective of diagnostic model and results in a low rate of OGTTs.

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