Influence of the Pre-pregnancy Diabetes Mellitus Management Model Based on the Internet of Things Technology Combined With the Paradigmatic Diagnosis and Treatment Management Model on the Pregnancy Outcome.

Context: Pre-gestational diabetes mellitus is a significant health concern associated with an increased rate of health complications in newborns and mothers. Effectively strengthening the management of pregnancy, controlling mothers' blood-sugar levels, and ensuring the safety of mothers and children are factors that needs attention.

Objective: The study intended to explore the effects on pregnancy outcomes of a new integrated management model of pre-pregnancy diabetes that uses the Internet of Things technology, combined with typical diagnosis and treatment, to improve maternal and fetal outcomes.

Design: The research team conducted a prospective cohort study.

Setting: The study took place in the Department of Obstetrics at Shanghai Sixth People's Hospital in Shanghai, China.

Participants: Participants were 173 pregnant women at the hospital who had received a diagnosis of gestational diabetes mellitus between January 2020 and December 2022.

Interventions: The research team divided participants into two groups: (1) the joint management group, the intervention group, with 87 participants, and (2) the traditional management group, the control group, with 86 participants. Both groups received standardized treatment and nutritional intervention, and the joint management group also received treatment under the new management mode, the Internet of Things.

Outcome Measures: The research team examined: (1) blood-glucose compliance-fasting blood glucose and 2 h postprandial blood glucose; (2) comparison of treatment compliance between the groups; (3) pregnancy outcomes, (4) newborn outcomes, (5) patient satisfaction; and (6) lipid metabolism, including triglycerides (TG), high-density lipoproteins (HDL), total cholesterol (TCH) free fatty acid (FFA).

Results: Compared to the traditional management group, the joint management group's: (1) fasting blood glucose and 2 h postprandial blood glucose were significantly lower than those of traditional management group (P < .0001); (2) treatment compliance was significantly higher (P < .05); (3) incidences of cesarean sections (P = .0069) and fetal distress (P = .0145) were significantly lower, (4) incidences of macrosomia and neonatal hypoglycemia were significantly lower (P < .05); (5) patient satisfaction rate was significantly higher (P = .0023) and (6) TG (P < .0001), LDL (P < .0001), and FFA (P = .0011) were significantly lower and HDL (P < .0001) was significantly higher.

Conclusions: The management mode that combined the Internet of Things platform with standardized diagnosis and treatment of pregnant women with gestational diabetes mellitus had good compliance and high patient satisfaction and could reduce maternal and infant complications; it's worthy of clinical promotion.