OBJECTIVE SMART-GDM examined whether Habits-GDM, a smartphone application (app) coaching program, can prevent excessive gestational weight gain (EGWG) and improve glycemic control and maternal and neonatal outcomes in gestational diabetes mellitus (GDM). RESEARCH DESIGN AND METHODS In this randomized controlled trial, women diagnosed with GDM between 12 and 30 weeks were randomly assigned to usual care (control) or to additional support from Habits-GDM that integrated dietary, physical activity, weight, and glucose monitoring (intervention). The primary outcome was the proportion of participants with EGWG. Secondary outcomes included absolute gestational weight gain (GWG), glycemic control, and maternal, delivery, and neonatal outcomes. RESULTS In total, 340 women were randomized (170 intervention, 170 control; mean ± SD age 32.0 ± 4.2 years; mean BMI 25.6 ± 5.6 kg/m 2 ). There were no statistically significant differences in the proportions of women with EGWG, absolute GWG, or maternal and delivery outcomes between experimental groups. Average glucose readings were lower in the intervention group (mean difference −0.15 mmol/L [95% CI −0.26; −0.03], P = 0.011) as were the proportions of glucose above targets (premeal: 17.9% vs. 23.3%, odds ratio 0.68 [95% CI 0.53; 0.87], P = 0.003; 2-h postmeal: 19.9% vs. 50%, 0.54 [0.42; 0.70], P < 0.001). When regarded as a composite (although not prespecified), the overall neonatal complications (including birth trauma, neonatal hypoglycemia, hyperbilirubinemia, respiratory distress, neonatal intensive care unit admission, and perinatal death) were significantly lower in the intervention group (38.1% vs. 53.7%, 0.53 [0.34; 0.84], P = 0.006). CONCLUSIONS When added to usual care, Habits-GDM resulted in better maternal glycemic control and composite neonatal outcomes (nonprespecified) but did not reduce EGWG among women with GDM.

The prevalence of gestational diabetes mellitus (GDM) is increasing, and only a few mobile health (mHealth) applications are specifically designed to manage GDM. In this mixed-methods study, a follow-up study of a randomized controlled trial (RCT) analyzed a largely automated mHealth application-based lifestyle coaching program to (a) measure the application’s usage behavior and (b) explore users’ perceptions of its usefulness in GDM management. Quantitative data were collected from the 170 application users who had participated in the intervention arm of the RCT. Semi-structured interviews (n = 14) captured users’ experiences when using the application. Data were collected from June 2019 to January 2020. Quantitative data were analyzed descriptively, and interviews were analyzed thematically. Only 57/170 users (34%) logged at least one meal, and only 35 meals on average were logged for eight weeks because of the incorrectly worded food items and limited food database. On the contrary, an average of 1.85 (SD = 1.60) weight values were logged per week since the weight tracking component was easy to use. Many users (6/14 (43%)) mentioned that the automatic coach messages created an immediate sense of self-awareness in food choices and motivated behavior. The findings suggest that for GDM management, a largely automated mHealth application has the potential to promote self-awareness of healthy lifestyle choices, reducing the need for intensive human resources. Additionally, several gaps in the application’s design were identified which need to be addressed in future works.

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BackgroundA syndrome of young‐onset diabetes mellitus associated with microcephaly, epilepsy and intellectual disability caused by mutations in the tRNA methyltransferase 10 homologue A (TRMT10A) gene has recently been described.Case reportWe report two siblings from the fourth family reported to have diabetes mellitus as a result of a TRMT10A mutation. A homozygous nonsense mutation p.Glu27Ter in TRMT10A was identified using targeted next‐generation sequencing and confirmed by PCR/Sanger sequencing. Diabetes was diagnosed while the subjects were in their 20s and was characterized by insulin resistance. Epilepsy and intellectual disability were features in common. Mild microcephaly was present at birth but their final head circumferences were normal.ConclusionOur report provides independent confirmation of the role of TRMT10A mutations in this syndrome and expands its phenotypic description. TRMT10A sequencing should be considered in children or adults with young‐onset diabetes who have a history of intellectual disability, microcephaly and epilepsy. This report also shows the advantages of using a targeted panel to identify previously unsuspected monogenic diabetes among young‐onset non‐insulin‐dependent diabetes in the absence of obesity and autoimmunity.