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Background The association between assisted reproductive technologies (ARTs) and the body mass index (BMI) of children remains controversial. Confounding by morbidity and other factors associated with parental infertility may have biased studies comparing children born after ART with children born after no treatment. We investigated the associations between different fertility treatments and BMI in children at age 5 to 8 years, adjusting for and stratifying by causes of parental infertility. Methods and findings This Danish cohort study included 327,301 children born between 2007 and 2012 (51% males, median age at follow-up 7 years). Of these, 13,675 were born after ART, 7,728 were born after ovulation induction with or without intrauterine insemination [OI/IUI], and 305,898 were born after no fertility treatments. Using the International Obesity Task Force (IOTF) standards, we defined overweight (BMI [greater than or equal to] IOTF-25) and obesity (BMI [greater than or equal to] IOTF-30). We compared children born after ART versus OI/IUI; intracytoplasmic sperm injection (ICSI) versus conventional in vitro fertilization (IVF); and frozen-thawed versus fresh embryo transfer and estimated crude and adjusted prevalences of children with overweight or obesity at age 5 to 8 years, prevalence odds ratios (PORs), and differences in mean BMI z-scores. Adjustment was performed using stabilized inverse probability of treatment weights, including parity, year of conception, parental causes of infertility, age, educational level, comorbidities, maternal country of origin, BMI, and smoking as covariates. The crude prevalence of obesity was 1.9% in children born after ART, 2.0% in those born after OI/IUI, and 2.7% in those born after no fertility treatment. After adjustment, children born after ART and OI/IUI had the same prevalence of being overweight (11%; POR 1.00, 95% confidence interval [CI] 0.91 to 1.11; p = 0.95) or obese (1.9%; POR 1.01, 95% CI 0.79 to 1.29; p = 0.94). Comparison of ICSI with conventional IVF yielded similar pattern (POR 0.95, 95% CI 0.83 to 1.07; p = 0.39 for overweight and POR 1.16, 95% CI 0.84 to 1.61; p = 0.36 for obesity). Obesity was more prevalent after frozen-thawed (2.7%) than fresh embryo transfer (1.8%) (POR 1.54, 95% CI 1.09 to 2.17; p = 0.01). The associations between fertility treatments and BMI were only modestly different in subgroups defined by the cause of infertility. Study limitations include potential residual confounding, restriction to live births, and lack of detailed technical information about the IVF procedures. Conclusions We found no association with BMI at age 5 to 8 years when comparing ART versus OI/IUI or when comparing ICSI versus conventional IVF. However, use of frozen-thawed embryo transfer was associated with a 1.5-fold increased risk of obesity compared to fresh embryo transfer. Despite an elevated relative risk, the absolute risk difference was low., Author(s): Kristina Laugesen 1,*, Katalin Veres 1, Sonia Hernandez-Diaz 2, Yu-Han Chiu 2,3, Anna Sara Oberg 2,4, John Hsu 5,6,7, Paolo Rinaudo 8, Mandy Spaan 9, Flora van Leeuwen 9, [...]

OBJECTIVE: We emulated a modified randomized trial (Metformin in Women With Type 2 Diabetes in Pregnancy [MiTy]) to compare the perinatal outcomes in women continuing versus discontinuing metformin during pregnancy among those with type 2 diabetes treated with metformin plus insulin before pregnancy. RESEARCH DESIGN AND METHODS: This study used two health care claims databases (U.S., 2000–2020). Pregnant women age 18–45 years with type 2 diabetes who were treated with metformin plus insulin at conception were eligible. The primary outcome was a composite of preterm birth, birth injury, neonatal respiratory distress, neonatal hypoglycemia, and neonatal intensive care unit admission. Secondary outcomes included the components of the primary composite outcome, gestational hypertension, preeclampsia, maternal hypoglycemia, cesarean delivery, infants large for gestational age, infants small for gestational age (SGA), sepsis, and hyperbilirubinemia. We adjusted for potential baseline confounders, including demographic characteristics, comorbidities, and proxies for diabetes progression. RESULTS: Of 2,983 eligible patients, 72% discontinued use of metformin during pregnancy. The average age at conception was 32 years, and the prevalence of several comorbidities was higher among continuers. The risk of the composite outcome was 46% for continuers and 48% for discontinuers. The adjusted risk ratio was 0.92 (95% CI 0.81, 1.03). Risks were similar between treatments and consistent between databases for most secondary outcomes, except for SGA, which was elevated in continuers only in the commercially insured population. CONCLUSIONS: Our findings were consistent with those reported in the MiTy randomized trial. Continuing metformin during pregnancy was not associated with increased risk of a neonatal composite adverse outcome. However, a possible metformin-associated risk of SGA warrants further consideration. [ABSTRACT FROM AUTHOR]

Fertility procedures recorded in health-care databases can be used to estimate the start of pregnancy, which can serve as a reference standard to validate gestational age estimates based on International Classification of Diseases codes. In a cohort of 17 398 US MarketScan pregnancies (2011-2020) in which conception was achieved via fertility procedures, we estimated gestational age at the end of pregnancy using algorithms based on (1) time (days) since the fertility procedure (the reference standard); (2) International Classification of Diseases, Ninth Revision (ICD-9)/ International Classification of Diseases, Tenth Revision (ICD-10) (before/after October 2015) codes indicating gestational length recorded at the end of pregnancy (method A); and (3) ICD-10 end-of-pregnancy codes enhanced with Z3A codes denoting specific gestation weeks recorded at prenatal visits (method B). We calculated the proportion of pregnancies with an estimated gestational age falling within 14 days (⁠|$\pm$| 14 days) of the reference standard. Method A accuracy was similar for ICD-9 and ICD-10 codes. After 2015, method B was more accurate than method A: For term births, within–14-day agreement was 90.8% for method A and 98.7% for method B. Corresponding estimates were 70.1% and 95.6% for preterm births; 35.3% and 92.6% for stillbirths; 54.3% and 64.2% for spontaneous abortions; and 16.7% and 84.6% for elective terminations. ICD-10–based algorithms that incorporate Z3A codes improve the accuracy of gestational age estimation in health-care databases, especially for preterm births and non–live births. [ABSTRACT FROM AUTHOR]

Metformin is a first-line pharmacotherapy for type 2 diabetes, but there is limited evidence about its safety in early pregnancy. This study examines women prescribed metformin before pregnancy and estimates the risk of continuing metformin and adding insulin versus starting insulin but discontinuing metformin in early pregnancy on outcomes of congenital malformations and nonlive births. Visual Abstract. Metformin Use in the First Trimester of Pregnancy and Risk for Nonlive Birth and Congenital Malformations: Emulating a Target Trial Using Real-World Data Metformin is a first-line pharmacotherapy for type 2 diabetes, but there is limited evidence about its safety in early pregnancy. This study examines women prescribed metformin before pregnancy and estimates the risk of continuing metformin and adding insulin versus starting insulin but discontinuing metformin in early pregnancy on outcomes of congenital malformations and nonlive births. Background: Metformin is a first-line pharmacotherapy for type 2 diabetes, but there is limited evidence about its safety in early pregnancy. Objective: To evaluate the teratogenicity of metformin use in the first trimester of pregnancy. Design: In an observational cohort of pregnant women with pregestational type 2 diabetes receiving metformin monotherapy before the last menstrual period (LMP), a target trial with 2 treatment strategies was emulated: insulin monotherapy (discontinue metformin treatment and initiate insulin within 90 days of LMP) or insulin plus metformin (continue metformin and initiate insulin within 90 days of LMP). Setting: U.S. Medicaid health care administration database (2000 to 2018). Participants: 12 489 pregnant women who met the eligibility criteria. Measurements: The risk and risk ratio of nonlive births, live births with congenital malformations, and congenital malformations among live births were estimated using standardization to adjust for covariates. Results: A total of 850 women were in the insulin monotherapy group and 1557 in the insulin plus metformin group. The estimated risk for nonlive birth was 32.7% under insulin monotherapy (reference) and 34.3% under insulin plus metformin (risk ratio, 1.02 [95% CI, 1.01 to 1.04]). The estimated risk for live birth with congenital malformations was 8.0% (CI, 5.7% to 10.2%) under insulin monotherapy and 5.7% (CI, 4.5% to 7.3%) under insulin plus metformin (risk ratio, 0.72 [CI, 0.51 to 1.09]). Limitation: Possible residual confounding by glycemic control and body mass index. Conclusion: Compared with switching to insulin monotherapy, continuing metformin and adding insulin in early pregnancy resulted in little to no increased risk for nonlive birth among women receiving metformin before pregnancy. Under conventional statistical criteria, anything between a 49% decrease and a 9% increase in risk for congenital malformations was highly compatible with our data. Primary Funding Source: National Institutes of Health. [ABSTRACT FROM AUTHOR]

We used design principles of target trial methodology to emulate the effect of sustained adherence to the Dietary Approaches to Stop Hypertension (DASH) diet on the 22-year risk of heart failure. Women and men aged 45–83 years without previous heart failure, who answered questionnaires in 1997 from the Swedish Mammography Cohort and the Cohort of Swedish Men, were eligible. Follow-up questionnaires were sent in 2008–2009. Incidence of heart failure was ascertained using the Swedish Patient Register, updated until December 31, 2019. The parametric g-formula was used to estimate the 22-year risk of heart failure under sustained adherence to a population-adapted DASH diet compared with no intervention. Intakes before 1997 for before-baseline adjustment was available only for women. In total, 31,238 women and 34,939 men were eligible. The 22-year risk of heart failure was 14.5% with long-term adherence to the DASH diet compared with 15.2% with no intervention (risk difference = −0.7%, 95% confidence interval: 1.6, 0.0%) in women and correspondingly in men 15.3% vs. 16.2% (risk difference = −0.9%, 95% confidence interval: −1.6, −0.2%). Our hypothetical intervention suggests that sustained adherence to the population-adapted DASH diet may reduce risk of heart failure in middle-aged and elderly Swedish women and men. [ABSTRACT FROM AUTHOR]

Background: Observational studies are often the only option to estimate effects of interventions during pregnancy. Causal inference from observational data can be conceptualized as an attempt to emulate a hypothetical pragmatic randomized trial: the target trial. Objective: To provide a step-by-step description of how to use healthcare databases to estimate the effects of interventions initiated during pregnancy. As an example, we describe how to specify and emulate a target trial of COVID-19 vaccination during pregnancy, but the framework can be generally applied to point and sustained strategies involving both pharmacologic and non-pharmacologic interventions. Methods: First, we specify the protocol of a target trial to evaluate the safety and effectiveness of vaccination during pregnancy. Second, we describe how to use observational data to emulate each component of the protocol of the target trial. We propose different target trials for different gestational periods because the outcomes of interest vary by gestational age at exposure. We identify challenges that affect (i) the target trial and thus its observational emulation (censoring and competing events), and (ii) mostly the observational emulation (confounding, immortal time, and measurement biases). Conclusion: Some biases may be unavoidable in observational emulations, but others are avoidable. For instance, immortal time bias can be avoided by aligning the start of follow-up with the gestational age at the time of the intervention, as we would do in the target trial. Explicitly emulating target trials at different gestational ages can help reduce bias and improve the interpretability of effect estimates for interventions during pregnancy. [ABSTRACT FROM AUTHOR]