Aims: In recent years, the prevalence of pregestational diabetes (PGDM) and the concern about the possibility of adverse pregnancy outcomes in affected women have been increasing. Routinely collected health data represent a timely and cost-efficient approach in PGDM epidemiological research. This study aims to evaluate the reliability of hospital discharge (HD) coding to identify a population-based cohort of pregnant women with PGDM and to assess trends in prevalence in two provinces of Northern Italy.
Methods: We selected all deliveries occurred in the period 1997-2010 with ICD-9-CM codes for PGDM in HD record and we matched up to 5 controls from mothers without diabetes. We used Diabetes Registers (DRs) as the gold standard for validation analysis.
Results: We selected 3800 women, 653 with diabetes and 3147 without diabetes. The agreement between HD records and DRs was 90.7%, with K=0.58. We detected 350 false positives and only 1 false negative. Sensitivity was 99.3%, specificity 90.0%, positive predictive value 46.4% and negative predictive value 99.9%. Of the false positives, 48.6% had gestational diabetes and 2.3% impaired glucose tolerance. After the validation process, PGDM prevalence decreased from 4.4 to 2.0 per 1000 deliveries.
Conclusions: Our results show that HD facilitate detection of almost all PGDM cases, but they also include a large number of false positives, mainly due to gestational diabetes. This misclassification causes a large overestimation of PGMD prevalence. Our findings require accuracy evaluation of ICD-9-CM codes, before they can be widely applied to epidemiological research and public health surveillance related to PGDM.
Keywords: Pregestational diabetes; Pregnancy; Registers; Routinely collected data.
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