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Updated: Jan 10, 2026

Improving IV Insulin Administration in a Community Hospital
Published on: June 11, 2012
Real-world use of non-pregnancy-specific automated insulin delivery systems during gestation and delivery: a case
Federica Carrieri1, Maria Pompea Antonia Baldassarre1, Sara Coluzzi2
1Department of Medicine and Aging Sciences, Center for Advanced Studies and Technology-CAST, University G. D'Annunzio of Chieti-Pescara, Via Luigi Polacchi 11/13, Chieti, 66100, Italy.
Background:
Maintaining optimal glycemic control in pregnant women with type 1 diabetes (T1D) remains a clinical challenge despite advancements in technology. Although not all automated insulin delivery (AID) systems are approved for gestational use, their use has increased in clinical practice. Limited real-world data exists on their effectiveness and safety throughout pregnancy as well as delivery.
Methods:
Retrospective case series including ten women with T1D who used AID systems (MiniMed 780G or Control-IQ) from preconception or early pregnancy through delivery at a single Italian Diabetes and Pregnancy Clinic between January 2020 and March 2025. Glucose metrics were analyzed from data-sharing portals across five time points (preconception, each trimester and delivery). Anthropometric data, safety and pregnancy outcomes were also evaluated.
Results:
Mean preconception HbA1c was 7.2 ± 1.0% and improved to 6.2 ± 0.3% by the third trimester. Time in range rose progressively, averaging 70.7 ± 11.2% in late pregnancy, with 5/10 individuals achieving the > 70% target. Coefficient of variation and time above range decreased with no severe hypoglycemia. Most women maintained AID mode during labor; mean TIRp at delivery was 70.1 ± 14.6%. Neonatal outcomes were generally favorable, with no stillbirths or neonatal deaths.
Conclusions:
AID systems can efficiently and safely support glycemic control during pregnancy and delivery in women with T1D when guided by expert teams and specific protocols. Although not currently approved for use during pregnancy, these systems may represent a viable alternative to pregnancy-specific algorithms.
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