Increased Maternal BMI at Time of Delivery Associated with Poor Maternal and Neonatal Outcomes.

OBJECTIVE: Current literature on the risks and outcomes of obesity in pregnancy almost exclusively utilizes prepregnancy body mass index (BMI). Given the rising obesity rate across the United States along with a paucity of available information on the relationship between delivery BMI and maternal and neonatal outcomes, our study aimed to determine the association of maternal BMI at delivery with antepartum, intrapartum, and neonatal complications at an academic referral hospital. STUDY DESIGN: This study is a secondary analysis of data collected for a prospective cohort study of Coronavirus Disease-2019 (COVID-19) in pregnancy. This analysis included all patients who delivered term singleton infants between May 1, 2020, and April 30, 2021, at the University of Iowa Hospitals and Clinics. Demographic and clinical data were obtained from the electronic medical record. The relationship between maternal BMI and maternal and neonatal characteristics of interest was assessed using logistic regression models. A statistical significance threshold of 0.05 was used for all comparisons. RESULTS: There were 1,996 women who delivered term singleton infants during the study period. The median BMI at delivery was 31.7 kg/m2 (interquartile range 27.9, 37.2), with 61.1% of women having a BMI ≥ 30.0 kg/m2. Increasing BMI was significantly associated with nonreassuring fetal status, unscheduled cesarean birth, overall cesarean birth rate, postpartum hemorrhage, prolonged postpartum stay, hypertensive diseases of pregnancy, neonatal hypoglycemia, neonatal intensive care unit admission, decreased APGAR score at 1 minute, and increasing neonatal birth weight. Even when controlling for preexisting hypertension in a multivariate model, increasing BMI was associated with gestational hypertension and preeclampsia. CONCLUSION: Increased maternal BMI at delivery was associated with adverse perinatal outcomes. These findings have implications for clinical counseling regarding risks of pregnancy and delivery for overweight and obese patients and may help inform future studies to improve safety, especially by examining reasons for high cesarean rates. KEY POINTS: · Sixty-one percent of delivering patients had a BMI330 kg/m2 at delivery.. · There was a higher cesarean rate with increasing delivery BMI.. · For every 5-unit increase in maternal BMI, neonatal weight increased by 0.47 g..

Predictors of Postpartum Hemorrhage and Associated Outcomes at a Midwest Academic Medical Center.

Background: Postpartum hemorrhage (PPH) remains a significant cause of maternal morbidity and mortality around the world, with rates increasing in the United States. The objective of this study was to determine predictors of, and outcomes associated with, PPH at a Midwest academic health center. Methods: Demographic and clinical data were obtained from the electronic medical record on all consecutive delivering patients between May 1, 2020, and April 30, 2021. Associations between PPH and perinatal characteristics and outcomes were assessed using logistic regression models. A significance threshold of 0.05 was used for all comparisons. Results: Of the 2497 delivering patients during the study period, 437 (18%) experienced PPH. Chronic hypertension, gestational hypertension, and preeclampsia with and without severe features were all associated with increased odds of PPH (odds rations [ORs], respectively, 1.61 (95% CI:1.13-2.24, p = 0.006), 1.62 (95% CI 1.18-2.21, p = 0.003), 1.81 (95% CI 1.14-2.80, p ≤ 0.001), and 1.92 (95% CI 1.29-2.82, p = 0.009). There were also increased odds of PPH with type I diabetes: 2.83 (95% CI 1.45-5.30, p = 0.001), type II diabetes: 2.14 (95% CI 1.15-3.82, p = 0.012), twin delivery: 3.20 (95% CI 2.11-4.81, p ≤ 0.001), cesarean delivery: 5.66 (95% CI 4.53-7.09, p ≤ 0.001), and assisted vaginal delivery: 3.12 (95% CI1.95-4.88, p ≤ 0.001). Infants of mothers with PPH had high odds of NICU admission (CI = 1.34-2.07, p < 0.001) and hypoxic ischemic encephalopathy (CI = 1.64-7.14, p < 0.001). Conclusion: Our findings confirm previous literature that preexisting and pregnancy-related hypertension, diabetes mellitus, multiple gestation, cesarean delivery, and assisted vaginal delivery are important predictors of PPH. In addition, we found that neonates of mothers with PPH had more adverse outcomes. These results may help to inform clinical care as rates of PPH continue to rise in the United States.

Evaluation of ChatGPT for Pelvic Floor Surgery Counseling.

IMPORTANCE: Large language models are artificial intelligence applications that can comprehend and produce human-like text and language. ChatGPT is one such model. Recent advances have increased interest in the utility of large language models in medicine. Urogynecology counseling is complex and time-consuming. Therefore, we evaluated ChatGPT as a potential adjunct for patient counseling. OBJECTIVE: Our primary objective was to compare the accuracy and completeness of ChatGPT responses to information in standard patient counseling leaflets regarding common urogynecological procedures. STUDY DESIGN: Seven urogynecologists compared the accuracy and completeness of ChatGPT responses to standard patient leaflets using 5-point Likert scales with a score of 3 being "equally accurate" and "equally complete," and a score of 5 being "much more accurate" and much more complete, respectively. This was repeated 3 months later to evaluate the consistency of ChatGPT. Additional analysis of the understandability and actionability was completed by 2 authors using the Patient Education Materials Assessment Tool. Analysis was primarily descriptive. First and second ChatGPT queries were compared with the Wilcoxon signed rank test. RESULTS: The median (interquartile range) accuracy was 3 (2-3) and completeness 3 (2-4) for the first ChatGPT query and 3 (3-3) and 4 (3-4), respectively, for the second query. Accuracy and completeness were significantly higher in the second query (P < 0.01). Understandability and actionability of ChatGPT responses were lower than the standard leaflets. CONCLUSIONS: ChatGPT is similarly accurate and complete when compared with standard patient information leaflets for common urogynecological procedures. Large language models may be a helpful adjunct to direct patient-provider counseling. Further research to determine the efficacy and patient satisfaction of ChatGPT for patient counseling is needed.

Effects of rurality and distance to care on perinatal outcomes over a 1-year period during the COVID-19 pandemic.

PURPOSE: Our aim was to investigate the roles of rurality and distance to care on adverse perinatal outcomes and COVID-19 seroprevalence at the time of delivery over a 1-year period. METHODS: Data were collected from the electronic medical record on all pregnant patients who delivered at a single, large, Midwest academic medical center over 1 year. Rurality was classified using standard Rural-Urban Commuting Area codes. Geographic Information System tools were used to map outcomes. Data were analyzed with univariate and multivariate models, controlling for Body Mass Index (BMI), insurance status, and parity. FINDINGS: A total of 2,497 patients delivered during the study period; 20% of patients were rural (n = 499), 18.6% were micropolitan (n = 466), and 61.4% were metropolitan (n = 1,532). 10.4% of patients (n = 259) were COVID-19 seropositive. Rural patients did not experience higher rates of any measured adverse outcomes than metropolitan patients; micropolitan patients had increased odds of preterm labor (OR = 1.41, P = .022) and pre-eclampsia (OR = 1.78, P<.001). Patients living 30+ miles away from the medical center had increased odds of preterm labor (OR = 1.94, P<.001), pre-eclampsia (OR = 1.73, P = .002), and infant admission to the neonatal intensive care unit (OR = 2.12, P<.001), as well as lower gestational age at delivery (ß = -9.2 days, P<.001) and birth weight (ß = -206 grams, P<.001). CONCLUSION: Distance to care, rather than rurality, was the key predictor of multiple adverse perinatal outcomes in this cohort of deliveries over a 1-year period. Our study suggests that rurality should not be used as a standalone indicator of access to care without further knowledge of the specific barriers affecting a given population.