Introduction: The prevalence of opioid use disorder (OUD) in pregnancy increased nearly five-fold over the past decade. Despite this, obstetric providers are less likely to treat pregnant women with medication for OUD than non-obstetric providers (75% vs 91%). A major reason is many obstetricians feel unprepared to prescribe medication for opioid use disorder (MOUD). Education and support may increase prescribing and overall comfort in delivering care for pregnant women with OUD, but optimal models of education and support are yet to be determined. Methods and analysis: We describe the rationale and conduct of a matched-pair cluster randomized clinical trial to compare the effectiveness of two models of support for reproductive health clinicians to provide care for pregnant and postpartum women with OUD. The primary outcomes of this trial are patient treatment engagement and retention in OUD treatment. This study compares two support models: 1) a collaborative care approach, based upon the Massachusetts Office-Based-Opioid Treatment Model, that provides practice-level training and support to providers and patients through the use of care managers, versus 2) a telesupport approach based on the Project Extension for Community Healthcare Outcomes, a remote education model that provides mentorship, guided practice, and participation in a learning community, via video conferencing. Discussion: This clustered randomized clinical trial aims to test the effectiveness of two approaches to support practitioners who care for pregnant women with an OUD. The results of this trial will help determine the best model to improve the capacity of obstetrical providers to deliver treatment for OUD in prenatal clinics. Trial registration: Clinicaltrials.gov trial registration number: NCT0424039. Trial registration: ClinicalTrials.gov NCT04240392.

AIM: To evaluate the association between gestational weight gain (GWG) in early pregnancy and incidence of abnormal glucose tolerance (AGT) and gestational diabetes mellitus (GDM) among Latinas. METHODS: We conducted a retrospective cohort study of 2039 Latinas using pooled data from two medical centres in Massachusetts. Gestational weights were abstracted from medical records and GWG was categorized as low, appropriate and excessive according to 2009 Institute of Medicine Guidelines. Diagnosis of AGT and GDM was confirmed by study obstetricians. RESULTS: A total of 143 women (7.0%) were diagnosed with GDM and 354 (17.4%) with AGT. After adjusting for age and study site, women with low GWG up to the time of GDM screen had a lower odds of GDM (OR: 0.51, 95% CI: 0.29-0.92). Among overweight women, women with excessive first-trimester GWG had 2-fold higher odds of AGT (OR: 1.96, 95% CI: 1.17-3.30) and GDM (OR: 2.07, 95% CI: 1.04-4.12) compared to those with appropriate GWG; however, these findings were not significant among normal weight or obese women. CONCLUSION: Among Latinas, low GWG up to the time of GDM screen was associated with lower odds of AGT and GDM, while excessive GWG among overweight women was associated with higher odds. Findings highlight need for interventions in early pregnancy to help women meet GWG guidelines and to moderate GWG among overweight Latinas.

Background: Gestational diabetes mellitus (GDM) complicates 4–7% of U.S. pregnancies. Diabetes and obesity rates are consistently higher in Hispanics compared to non-Hispanic whites. Early-to-mid gestational weight gain (GWG) has been thought to be associated with GDM risk; however, the Institute of Medicine (IOM) found insufficient evidence when re-examining GWG guidelines in 2009. Objective: To investigate associations of GWG adherence per 2009 IOM guidelines prior to 1-hr 50g Glucose Tolerance Test (GTT), or glucola, with GDM diagnoses in Latinas. Methods: The study is a retrospective chart review of all Hispanic women delivered by UMass Memorial faculty between 4/1/06-3/31/11 and received prenatal care at faculty-resident practices (n=1163). Pre-pregnancy weight and height, weight and gestational age (GA) most proximate to glucola and 100g GTT where appropriate, lab results and relevant demographics were abstracted. Weight gain was categorized as inadequate, appropriate or excessive according to 2009 IOM Guidelines with adjustment for gestational age. Mean and standard deviation (SD) and frequency measures reported for continuous and categorical variables, respectively. Comparisons were evaluated with chi-squared tests with statistical significance set at p<0.05. Results: Data for 1115 subjects was analyzed. Preliminary cohort was mean age 25.3 years (sd±6.0), mean gravidity 2.8 (sd±1.8) and 72.1% English and 26.4% Spanish-speaking. Eleven subjects excluded for pregestational diabetes. BMI calculable for 858 subjects (5.4% underweight, 40.3% normal, 26.0% overweight and 28.3% obese); 70 subjects missing GWG prior to glucola. Seven hundred eighty-eight subjects had complete data, on which remainder of analyses were performed. By 2009 IOM guidelines, 174 (22.1%), 193 (24.5%) and 421 (53.4%) gained inadequately, appropriately and excessively as per BMI criteria, respectively. Overall, 86 of 788 diagnosed with GDM (10.9%). According to weight gain adherence, 14 of 174 (8.0%) inadequate-gainers, 20 of 193 (10.4%) appropriate-gainers and 52 of 421 (12.4%) excessive-gainers were diagnosed with GDM. Of subjects with GDM diagnosis (n=86), 16.3%, 23.3% and 60.5% were inadequate, appropriate and excessive-gainers, respectively. Compared to appropriate gainers, the crude odds ratio and 95% CI for GDM diagnosis was 1.22 (0.71-2.11) for excessive-gainers and 0.76 (0.37-1.55) for inadequate-gainers. No statistically significant association between pre-glucola GWG and GDM detected (p=0.3). Conclusion: The rate of GDM in this cohort of Latina women is almost double that of the general population. Though no statistically significant association was identified, the majority of patients diagnosed with GDM were classified as excessive-gainers as per pre-glucola GWG adherence. The trend warrants further evaluation of this population at increased risk for GDM as well as analysis within high-risk subgroups.