The relationship between timing of screening for gestational diabetes mellitus and maternal and fetal outcomes: A retrospective cohort study linking primary care electronic and hospital administrative data

Helena Piccinini-Vallis , Mathew Grandy , Lynn Bussey , Jillian Coolen , Sarah Sabri
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Abstract

Background

Gestational diabetes (GDM) is associated with adverse outcomes including a large-for-gestational age (LGA) baby, which in turn is associated with downstream childhood obesity. Appropriate timing of GDM screening is important for prompt initiation and optimization of medical management, potentially mitigating the risk of those outcomes. The present study explored the association between the timing of GDM screening and macrosomia, LGA, shoulder dystocia and caesarean section.

Methods

This retrospective cohort study linked primary care prenatal data and intrapartum data from a provincial hospital administrative database. Women with singleton pregnancies who received prenatal care between July 1, 2019 and December 31, 2022 and who also delivered within that timeframe were included in the study.

Results

198 participants were linked between the databases. Among participants for whom GDM risk could be calculated (n = 180), 30.6 % had late GDM screening. Unadjusted logistic regression models showed that late screening for GDM was associated with higher likelihood of LGA (OR = 2.89; 95 % CI = 1.19–7.04; p = 00.019). Adjusted models showed that the best predictor of macrosomia, LGA, and shoulder dystocia was excess gestational weight gain (GWG) (OR = 3.26, CI = 1.17–9.10, p = 0.024; OR 3.00, 95 % CI 0.91–9.93, p = 00.072; and OR = 3.52, CI = 0.83–14.84, p = 00.087 respectively); the best predictor of caesarean section was pre-pregnancy BMI (OR = 2.86; CI = 1.12 = 7.27; p = 0.028).

Conclusions

Almost one-third of participants had screening later than recommended, and late screening for GDM was associated with a higher likelihood of LGA. Linking longitudinal prenatal primary care data to hospital administrative data creates opportunities for future studies pertaining to prenatal care, potentially resulting in improvements in the care provided to vulnerable populations experiencing disproportionate rates of pre-pregnancy obesity and excess GWG.

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