Pregnancy (Hoboken, N.J.) · 2026
Pregnancy and glycemic outcomes with hybrid closed-loop insulin delivery versus sensor-augmented pump therapy among women with type 1 diabetes.
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Brewton Annabeth, Pandit Radhika, Wu Jiqiang, Santhanam Natasha, Privitera Ellena, Vickers Shaylyn, Gabbe Steven, Grobman William A, Landon Mark B, Field Christine P, Buschur Elizabeth O, Venkatesh Kartik K
Аннотация
OBJECTIVE: Pregnant women with type 1 diabetes (T1D) increasingly utilize hybrid closed-loop (HCL) pumps, but pregnancy-specific algorithms in many countries including the United States are not available. We compared pregnancy and glycemic outcomes between those intending to use off-label automated HCL versus manual sensor-augmented pump therapy (SAPT).
METHODS: We conducted a single-center retrospective study from 2022 to 2025. The exposure was intent to use HCL using non-pregnancy algorithms versus SAPT (reference) at the start of pregnancy. Outcomes included pregnancy outcomes (cesarean delivery, preeclampsia, preterm birth, small- and large-for-gestational-age, neonatal intensive care unit admission, neonatal hypoglycemia, neonatal hyperbilirubinemia, and respiratory distress syndrome) and glycemic measures the week before delivery (hemoglobin A1c and continuous glucose monitor metrics including time in range within a pregnancy-specific range [63-140 mg/dL], time above and below range, standard deviation, and mean glucose). An Inverse-Probability-of-Treatment Weighting analytic approach was used.
RESULTS: Among 154 women with T1D, 68.2% intended to use HCL and 31.8% SAPT when initiating prenatal care (median gestational age of 8.0 weeks [interquartile range {IQR}, 7.3, 9.3]). In adjusted analyses, women using HCL had neonates with a higher birthweight (3640 vs. 3430 g; adj. beta, 271.98; 95% CI, 0.31, 543.65) and mean sensor glucose the week prior to delivery (150.0 vs. 145.0 mg/dL; adj. beta, 13.36; 95% CI, 0.79, 25.93) and lower time below range compared with those using SAPT (2.0 vs. 4.0%; adj. beta, -3.73; 95% CI, -6.52, -0.93). Other pregnancy and glycemic outcomes did not differ between groups.
CONCLUSION: Among a US cohort with T1D enrolled in a prenatal and diabetes care program, pregnancy and glycemic outcomes were similar between those using off-label HCL versus SAPT. Evaluating how HCL with pregnancy-specific algorithms can be used to promote maternal and child health could be most helpful for pregnant women with T1D and should be a research priority.
METHODS: We conducted a single-center retrospective study from 2022 to 2025. The exposure was intent to use HCL using non-pregnancy algorithms versus SAPT (reference) at the start of pregnancy. Outcomes included pregnancy outcomes (cesarean delivery, preeclampsia, preterm birth, small- and large-for-gestational-age, neonatal intensive care unit admission, neonatal hypoglycemia, neonatal hyperbilirubinemia, and respiratory distress syndrome) and glycemic measures the week before delivery (hemoglobin A1c and continuous glucose monitor metrics including time in range within a pregnancy-specific range [63-140 mg/dL], time above and below range, standard deviation, and mean glucose). An Inverse-Probability-of-Treatment Weighting analytic approach was used.
RESULTS: Among 154 women with T1D, 68.2% intended to use HCL and 31.8% SAPT when initiating prenatal care (median gestational age of 8.0 weeks [interquartile range {IQR}, 7.3, 9.3]). In adjusted analyses, women using HCL had neonates with a higher birthweight (3640 vs. 3430 g; adj. beta, 271.98; 95% CI, 0.31, 543.65) and mean sensor glucose the week prior to delivery (150.0 vs. 145.0 mg/dL; adj. beta, 13.36; 95% CI, 0.79, 25.93) and lower time below range compared with those using SAPT (2.0 vs. 4.0%; adj. beta, -3.73; 95% CI, -6.52, -0.93). Other pregnancy and glycemic outcomes did not differ between groups.
CONCLUSION: Among a US cohort with T1D enrolled in a prenatal and diabetes care program, pregnancy and glycemic outcomes were similar between those using off-label HCL versus SAPT. Evaluating how HCL with pregnancy-specific algorithms can be used to promote maternal and child health could be most helpful for pregnant women with T1D and should be a research priority.