Objective This study aimed to evaluate the prevalence of severe insulin resistance (insulin requirements ≥2 units/kg) at delivery and the relationship between severe insulin resistance, glycemic control, and adverse perinatal outcomes in pregnant women with type-2 diabetes mellitus. Study Design This is a retrospective cohort study of women with type-2 diabetes mellitus who delivered between January 2015 and December 2017 at a tertiary academic medical center. Maternal demographic information, self-monitored blood sugars, and insulin doses were abstracted from the medical record. Multivariable logistic regression was used to identify maternal baseline characteristics associated with severe insulin resistance at delivery. Results Overall 72/160 (45%) of women had severe insulin resistance. Women in the severe insulin resistance group demonstrated evidence of suboptimal glycemic control as evidenced by higher mean hemoglobin A1c (HbA1c) values (7.2 [ ± 1.1] vs. 6.6 [ ± 1.3%], p = 0.003), higher mean fasting (104.0 [ ± 17.4] vs. 95.2 [ ± 11.7 mg/dL], p < 0.001) and postprandial glucose values (132.4 [ ± 17.2] vs. 121.9 [ ± 16.9 mg/dL]), p < 0.001), and a higher percentage of total glucose values that were elevated above targets (37.7 [95% confidence interval (CI): 26.8–50] vs. 25.6 [95% CI: 13.3–41.3%], p < 0.001). Maternal HbA1c ≥6.5% and insulin use prior to pregnancy were associated with a higher prevalence of severe insulin resistance, while Hispanic ethnicity and non-White race were associated with a lower prevalence of severe insulin resistance. The rates of adverse perinatal outcomes including large for gestational age (LGA) birth weight, cesarean delivery, and hypertensive disorders of pregnancy did not differ between groups. Conclusion Severe insulin resistance is common among pregnant women with type-2 diabetes, and it is associated with suboptimal glycemic control. Future studies are necessary to develop strategies to identify women with severe insulin resistance early in pregnancy and facilitate adequate insulin dosing. Key Points
Type 2 diabetes mellitus (DM) is associated with adverse perinatal outcomes, but insulin requirements and the prevalence of inadequate glycemic control across gestation are not well characterized. We therefore conducted a retrospective cohort study of women with type 2 DM who delivered from 2015 to 2017. Self-monitored blood glucose and insulin doses across gestation were abstracted, and inadequate glycemic control was defined as a mean blood glucose >95 mg/dL fasting or >140 mg/dL 1 hour post-prandial. We compared insulin dosing in early gestation and at delivery by maternal glycemic control. Multivariable logistic regression was used to identify predictors of high insulin requirements at delivery. Inadequate glycemic control occurred in 96/155 (62%) of women. Maternal BMI, gestational age at first prenatal visit, and duration of diabetes were similar between women with inadequate and adequate control. Baseline HbA1c (8.1 ±2.0 vs. 7.5 ±1.9%, p=0.10) and percent of women receiving medical therapy before initiation of prenatal care (71.3% vs. 69.5%, p=0.81) were also similar between groups. Women with inadequate and adequate control had similar insulin doses in early pregnancy (0.7 ±0.5 vs. 0.7 ±0.5 units/kg, p=0.86), but by delivery women with inadequate control required significantly higher doses (2.3 ±1.2 vs. 1.8 ±1.0 units/kg, p=0.004). The highest quartile of insulin dose at delivery was >2.7 units/kg. Multivariable logistic regression modeling demonstrated that maternal BMI at the first prenatal visit (aOR 1.0, 95% CI 0.99-1.01), non-white race (aOR 0.35, 95% CI 0.16-0.78), and baseline HbA1c (aOR 1.22, 95% CI 1.02-1.46) had poor ability to predict high insulin requirements at delivery (AUC 0.67). Although high insulin requirements may be related to suboptimal glycemic control in women with type 2 DM, it is difficult to identify these women using baseline characteristics. Further studies are urgently needed to optimize insulin dosing in women with Type 2 DM. Disclosure H.C. Nadeau: None. M.E. Maxted: None. D. Madhavan: None. S. Pierce: None. M.N. Feghali: None. C.M. Scifres: None.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.