Dyre, Lillian

Objectives: To analyze the association between primary infertility and infertility type with the age of natural menopause. Methods: This is a retrospective cohort study reviewing a subset of women from the Mayo Primary Infertility Cohort (MPIC). The MPIC is a cohort of 1,001 women diagnosed with primary infertility and 1,001 age-matched referent women. In this study, we included all women at risk for natural menopause and further evaluated those who had reported natural menopause in the medical record. We compared the risk of natural menopause using Cox proportional hazard models with infertility status and infertility type as covariates. In those with documented menopause during the study period, the association between primary infertility and early and premature menopause was analyzed with χ 2 testing. We evaluated the association between age at natural menopause, primary infertility status, and infertility type in this group using linear regression. Results: In all, 461 women with primary infertility, with 530 referent individuals, were at risk of natural menopause, and of these, 340 women with infertility and 346 referent women underwent documented natural menopause on review of medical records. Women with primary infertility had an increased risk of natural menopause (hazard ratio: 1.25, 95% CI: 1.06-1.46) and underwent menopause 1 year earlier than referent individuals (β=−1.17, 95% CI: −1.82 to −0.52) after adjustment for body mass index, tobacco use, race, menstrual cycle regularity, and previous contraception use. Women with primary infertility were more likely to undergo early menopause (age 40-45) than referent women (7.6% vs. 3.0%, P =0.01). Compared with referent women, women with endometriosis underwent menopause 2.75 years earlier (95% CI: −4.38 to −1.13, P =0.0009), and women with unexplained infertility underwent menopause 1.45 years earlier (95% CI: −2.26 to −0.64, P =0.0005). Conclusions: Women with primary infertility had an increased risk of early menopause and collectively underwent menopause 1 year earlier than women without a history of primary infertility.

Abstract Patients with hypertensive disorders of pregnancy (HDPs) are recommended to attend an early postpartum follow-up visit for blood pressure monitoring. Follow-up frequency for patients with HDPs can vary widely, with some patients requiring multiple office visits. We sought to determine factors associated with multiple postpartum blood pressure visits among patients with HDPs. We retrospectively identified patients with HDPs who delivered at our maternity center in 2019 and compared factors between patients who attended a single blood pressure follow-up appointment without requiring further clinical evaluation for hypertension and patients who required multiple postpartum clinical evaluations for persistent hypertension. Univariate logistic regression models were used to identify factors associated with increased odds of having multiple clinically indicated postpartum visits for blood pressure monitoring. We identified 328 patients with HDPs, of whom 260 (79.3%) attended an initial postpartum blood pressure follow-up appointment and were included in further analyses. Of the 260 patients, 70 (26.9%) had multiple blood pressure visits. Factors associated with multiple blood pressure visits included delivery between 34 and less than 37 weeks of gestation (odds ratio [OR], 3.62; 95% CI, 1.07–12.30), systolic blood pressure before discharge of 140 mm Hg or higher (OR, 5.02; 95% CI, 2.57–9.82), and discharge with blood pressure medication (OR, 3.42; 95% CI, 1.82–6.41). Patients with HDPs who deliver preterm, have persistent hypertension before discharge, or are discharged with antihypertensive medication require continued close postpartum observation and continuity of care.

Abstract Objective To develop a comprehensive risk stratification model to identify patients at high risk of cesarean surgical site infection (cSSI) based on information available at the time of hospital discharge. Methods This is a retrospective cohort study based on datasets from two independent level IV academic medical centers to improve generalizability. The first study includes 2336 cesarean deliveries for analysis with 109 instances of cSSI (4.7%). The second study includes 2936 cesarean deliveries with 72 instances of cSSI (2.5%). The first study cohort was utilized for both model training and internal validation, using the 15 shared features present in both datasets. Random search with cross‐validation was used to choose the type of machine learning (ML) model and its hyperparameters, with area under the receiver operating characteristic curve (AUC) as the validation metric. The second study cohort was then used to evaluate testing accuracy (external validation) and generalization capability of this model. The predictive importance of each feature was evaluated using permutation importance applied to the second cohort. Risk stratification cutoff scores were defined based on centiles over the first patient cohort and evaluated on the second cohort. Results The ML model with the highest validation AUC was an XGBoost classifier. This trained model achieved an AUC of 0.78 on the training data and a 0.72 cross‐validated AUC. When tested on data from the second study cohort, it achieved an AUC of 0.69. The features showing the strongest predictive generalization, as measured by permutation importance, were length of hospital stay, primary indication for cesarean delivery, and estimated blood loss. Using the second cohort to test our model, the model shows a 22.7% positive predictive value (PPV) of cSSI among women in the highest risk group, and a 0.8% PPV among women in the bottom risk group, compared with 2.5% cSSI incidence for the study population at large. Conclusion We developed and validated a predictive ML model for cSSI with information available to healthcare professionals at the time of hospital discharge. This model suggests that the most predictive risk factors for cSSI include length of hospital stay, primary indication for cesarean delivery, and estimated blood loss. Additionally, the model provides reasonable risk stratifications for individual patients. This tool may be used for identifying subgroups at higher risk of cSSI and identifying those who may require closer surveillance or clinical intervention.

Studies have shown that prosection and dissection facilitate similar academic outcomes and promote meaningful learning in anatomy laboratory courses. While dissection is the mainstay of many graduate level anatomy curricula, financial and other constraints have increased the use of prosection. This research evaluates student preference for studying different body regions and accomplishing learning outcomes related to content knowledge, teamwork, career preparation, humanistic learning, and wellness. First‐year medical students (n=51) who completed a hybrid prosection and dissection course completed a post‐course survey about their perceptions of the effectiveness of each lab learning modality. Response options included prosection, dissection, no preference (equally effective), and no preference (equally ineffective). A one‐way ANOVA was used to evaluate performance differences on course assessments between students in the hybrid course and students in past years who participated in a dissection based course. The response rate was 51%. Respondents preferred dissection for learning the back (62%), thorax (68%), abdomen (54%), shoulder, axilla, and arm (61.5%), and hip, thigh, and leg (46%). Prosection was favored for the pelvis (perineum 81%, cavity 69%), foot (58%), hand (46%), and head/neck (64%). Students favored dissection for gaining hands‐on skills relevant to surgical practice, appreciating anatomical variation, becoming more comfortable handling the human body, engaging in self‐directed learning, and fostering teamwork. Respondents felt prosection provided more time for independent study and wellness activities. Prosection and dissection were rated equally effective for developing a medical vocabulary, applying anatomical knowledge to clinical conditions, and gaining a 3D appreciation of the body. A hybrid prosection and dissection course was preferred by 73% of respondents, compared to 4% who ranked prosection alone as their preference; no students ranked dissection alone as their first choice. There were no statistically significant differences in academic performance related to teaching methods (F(3,195) = 2.65, p=0.34) between students in the hybrid course and students in previous dissection only courses. Students prefer prosection for learning more spatially complex and intricate regions requiring time‐consuming and skilled dissection. However, learners recognize distinct benefits of dissection for acquiring various technical and non‐technical skills. Hybrid courses should capitalize on the strengths of each method, aligning instructional methods with outcomes and incorporating learner preferences to achieve meaningful, lasting learning.