Introduction: Laparoscopic salpingectomy is a commonly performed procedure and is often one of the first laparoscopic procedures performed by novice residents in Obstetrics and Gynecology (OB/GYN). Opportunities to practice before the operating room can be limited. Methods: We developed an animal tissue model and incorporated it into a laparoscopic salpingectomy simulation for OB/GYN residents in a single academic program. The simulation included a pre-simulation video describing the steps of laparoscopic salpingectomy, the laparoscopic salpingectomy simulation using an electrosurgical device, a post simulation survey, and debriefing with learner targeted feedback. Validity evidence for the simulation model was gathered using the Messick framework. Resident performance was assessed using the Objective Structured Assessment of Laparoscopic Salpingectomy (OSA-LS) and the Global Operative Assessment of Laparoscopic Skills (GOALS). Performance was correlated to the year of training with upper-level residents grouped for analysis. Results: Twenty-five simulations of laparoscopic salpingectomy were performed by 14 learners (first through fourth year). The tool was highly rated by participants. We found a significant correlation between the mean OSA-LS score and surgical experience. The mean GOALS score also increased with experience and was significantly different between 1st and 2nd years and between 1st and upper-level residents. A passing score of 12 was established for each assessment rubric. Discussion: This low-cost surgical model addresses a gap in simulation options for preoperative use of electrosurgical devices. This simulation can be used in OB GYN residency as a method to assess competency or provide feedback.

Importance Prepregnancy care and counseling optimize maternal health before conception to improve outcomes for mothers and infants. In the US, 66.4% of reproductive-aged women have at least 1 modifiable risk factor for adverse pregnancy outcomes. Observations For all individuals desiring pregnancy, recommended interventions include folic acid supplementation; cessation of tobacco, alcohol, cannabis, and opioids; immunizations against hepatitis B virus, varicella, and rubella; and screening for syphilis and HIV. Folic acid use before pregnancy is associated with reduced fetal neural tube defects (relative risk [RR], 0.67; 95% CI, 0.52-0.87). Maternal tobacco smoking is associated with increased risks of stillbirth (summary RR [sRR], 1.46; 95% CI, 1.38-1.54), neonatal death (sRR, 1.22; 95% CI, 1.14-1.30), and perinatal death (sRR, 1.33; 95% CI, 1.25-1.41). Screening for and treatment of syphilis and HIV prior to and during pregnancy decrease rates of fetal and neonatal infection. Prepregnancy immunizations against hepatitis B virus, varicella, and rubella decrease neonatal infection and mortality. Individuals using tobacco, alcohol, cannabis, and opioids should receive counseling and treatment prior to pregnancy (eg, buprenorphine or methadone for opioid use disorder). For individuals with chronic disease, routine health examinations and contraceptive care in the year before conception can optimize pregnancy timing and are associated with decreased risk of severe maternal morbidity. Compared with planned pregnancies, unintended pregnancies are associated with increased risk of postpartum depression (15.7% vs 9.6%; adjusted odds ratio [aOR], 1.51; 95% CI, 1.40-1.70), preterm birth (9.4% vs 7.7%; aOR, 1.21; 95% CI, 1.12-1.31), and low infant birth weight (7.3% vs 5.2%; aOR, 1.09; 95% CI, 1.02-1.21). Weight loss prior to conception is recommended for individuals with a body mass index of 25 or greater because overweight and obesity are associated with increased risk of gestational diabetes, gestational hypertension, and cesarean delivery. Among patients with pregestational diabetes (type 1 or 2), hemoglobin A 1c of less than 6.5% is associated with a decreased risk of fetal anomaly compared with hemoglobin A 1c of 6.5% or greater. Cardiovascular complications such as hypertension and heart failure occur in 15% of pregnancies and are more common among those with preexisting cardiovascular disease. These patients should receive counseling on maternal and neonatal risk, monitoring, and medication management by specialists in cardiology and maternal fetal medicine. Conclusions and Relevance Prepregnancy counseling and care reduce maternal morbidity and neonatal morbidity and mortality. Primary care–based discussion of reproductive goals, immunizations, screening for infections and substance use, and risk-reducing interventions such as folate supplementation can optimize outcomes in individuals contemplating pregnancy.

Importance:Prepregnancy care and counseling optimize maternal health before conception to improve outcomes for mothers and infants. In the US, 66.4% of reproductive-aged women have at least 1 modifiable risk factor for adverse pregnancy outcomes. Observations:For all individuals desiring pregnancy, recommended interventions include folic acid supplementation; cessation of tobacco, alcohol, cannabis, and opioids; immunizations against hepatitis B virus, varicella, and rubella; and screening for syphilis and HIV. Folic acid use before pregnancy is associated with reduced fetal neural tube defects (relative risk [RR], 0.67; 95% CI, 0.52-0.87). Maternal tobacco smoking is associated with increased risks of stillbirth (summary RR [sRR], 1.46; 95% CI, 1.38-1.54), neonatal death (sRR, 1.22; 95% CI, 1.14-1.30), and perinatal death (sRR, 1.33; 95% CI, 1.25-1.41). Screening for and treatment of syphilis and HIV prior to and during pregnancy decrease rates of fetal and neonatal infection. Prepregnancy immunizations against hepatitis B virus, varicella, and rubella decrease neonatal infection and mortality. Individuals using tobacco, alcohol, cannabis, and opioids should receive counseling and treatment prior to pregnancy (eg, buprenorphine or methadone for opioid use disorder). For individuals with chronic disease, routine health examinations and contraceptive care in the year before conception can optimize pregnancy timing and are associated with decreased risk of severe maternal morbidity. Compared with planned pregnancies, unintended pregnancies are associated with increased risk of postpartum depression (15.7% vs 9.6%; adjusted odds ratio [aOR], 1.51; 95% CI, 1.40-1.70), preterm birth (9.4% vs 7.7%; aOR, 1.21; 95% CI, 1.12-1.31), and low infant birth weight (7.3% vs 5.2%; aOR, 1.09; 95% CI, 1.02-1.21). Weight loss prior to conception is recommended for individuals with a body mass index of 25 or greater because overweight and obesity are associated with increased risk of gestational diabetes, gestational hypertension, and cesarean delivery. Among patients with pregestational diabetes (type 1 or 2), hemoglobin A1c of less than 6.5% is associated with a decreased risk of fetal anomaly compared with hemoglobin A1c of 6.5% or greater. Cardiovascular complications such as hypertension and heart failure occur in 15% of pregnancies and are more common among those with preexisting cardiovascular disease. These patients should receive counseling on maternal and neonatal risk, monitoring, and medication management by specialists in cardiology and maternal fetal medicine. Conclusions and Relevance:Prepregnancy counseling and care reduce maternal morbidity and neonatal morbidity and mortality. Primary care-based discussion of reproductive goals, immunizations, screening for infections and substance use, and risk-reducing interventions such as folate supplementation can optimize outcomes in individuals contemplating pregnancy.

STUDY OBJECTIVE:To determine the optimal hysteroscopic myomectomy technique by comparing symptomatic leiomyoma recurrence rates after mechanical tissue removal system vs bipolar resection. DESIGN:This retrospective cohort study included premenopausal patients undergoing fibroid resection with the hysteroscopic mechanical tissue removal system (mTRS) or bipolar resectoscope (BR) for International Federation of Gynecology and Obstetrics (FIGO) type 0-2 leiomyomas. Patients who underwent resection from 2005 to 2021 were followed over time for symptom recurrence and medical or surgical treatments. The risk of fibroid recurrence and hysterectomy was estimated using the Kaplan-Meier method. SETTING:Single academic tertiary care center. PATIENTS:Patients with FIGO type 0-2 leiomyomas at the time of surgery were included. Those without pathology-confirmed leiomyoma or for whom hysteroscopic resection was completed with an alternative or unknown method were excluded. Patients that were postmenopausal at the time of the study were excluded as well. INTERVENTIONS:Hysteroscopic Mechanical Tissue Removal System or Bipolar Resection. MEASUREMENTS AND MAIN RESULTS:In total, 89 patients were treated with the hysteroscopic mechanical tissue removal system and 358 with bipolar resection. Baseline demographics, including age, BMI, race/ethnicity, and obstetric history, were comparable between groups; abnormal uterine bleeding was the most common indication for index surgery. The mean fibroid size and median resected tissue volume were slightly greater in the bipolar resection group. The length of follow-up was variable, with a mean of 7.1 years (standard deviation, 5.4) among both groups. Symptomatic fibroid recurrence occurred in 29.2% of patients in the hysteroscopic mechanical tissue removal system compared to 38.5% in the bipolar resection group (p = NS). Additional hysteroscopic management, with a hysteroscopic mechanical tissue removal system or bipolar resection, was the most common method of treatment for fibroid recurrence. The cumulative incidence of hysterectomy was similar (mTRS = 15.7% vs BR = 22.3%), with abnormal uterine bleeding being the most common indication. CONCLUSION:There was no significant difference between long-term recurrence rates for FIGO type 0-2 leiomyomas when comparing the hysteroscopic mechanical tissue removal system to bipolar resection; however, larger prospective cohorts with longer follow-up or randomized controlled trials may help to determine if one technique is indeed more effective.

Hysteroscopy is one of the most essential tools of the practicing gynecologist. This work examines the progress of hysteroscopy through key categorical technological advances. We focus on 9 key innovations and how they continue to evolve and shape the practice of hysteroscopy, as well as considering implications and opportunities for future technology. Hysteroscopy has evolved from purely diagnostic applications to more advanced therapeutic options for the treatment of intrauterine pathology over the last century. Continued disruptive innovation to improve diagnostic accuracy and the ability to treat more advanced pathology is on the horizon.

The multi-center, international consortium on endometrial cancer held in January 2025 at Mayo Clinic in Rochester, Minnesota brought together leading experts in gynecologic oncology to explore the latest advancements in the understanding, diagnosis, and treatment of endometrial cancer. Discussions centered on key topics, including updates in molecular testing and disease staging, emerging treatment strategies for advanced and recurrent disease, fertility-sparing management, and critical pathology challenges, particularly, the assessment of lympho-vascular space invasion. Each topic was examined in dedicated working group sessions, fostering in-depth exchanges to identify research priorities and develop actionable strategies. This summary highlights the central themes and insights from the meeting, outlining a roadmap for future advancements in the field. By promoting inter-disciplinary collaboration, the meeting laid the foundation for future research, policy recommendations, and clinical innovations aimed at improving patient outcomes.

OBJECTIVE: To compare the performance of four commonly used algorithms to differentiate benign from malignant adnexal masses when used by a novice operator.METHODS: Women with adnexal masses treated at Mayo Clinic, Rochester, Minnesota, in 2019 were identified retrospectively. Patients were included if they underwent surgery within 3 months of diagnosis or had at least 10 months of follow-up. A nonexpert operator (European Federation of Societies for Ultrasound in Medicine and Biology level I) classified each lesion using ADNEX (Assessment of Different Neoplasias in the Adnexa), two-step strategy (benign descriptors followed by ADNEX), O-RADS (Ovarian-Adnexal Reporting and Data System) 2019, and O-RADS 2022. The primary outcome measure was the area under the receiver operating characteristic curve (AUC) compared across the four algorithms.RESULTS: A total of 556 women were included in the analyses: 452 with benign and 104 with malignant masses. The AUCs of ADNEX, the two-step strategy, O-RADS 2019, and O-RADS 2022 were 0.90 (95% CI, 0.87-0.94), 0.91 (95% CI,0.88-0.94), 0.88 (95% CI,0.84-0.91), and 0.88 95% CI, (0.84-0.91), respectively. The two-step strategy performed significantly better than the O-RADS algorithms (P=.005 and P=.002). With all the algorithms, the observed malignancy rate was 1.9-2.2% among lesions categorized as almost certainly benign, twofold higher than the expected less than 1.0%. Lesions wrongly classified as almost certainly benign were borderline tumors (n=4) and metastases (n=3).CONCLUSION: In the hands of a novice operator, all algorithms performed well and were able to distinguish benign from malignant lesions. Although the two-step strategy performed slightly better than the O-RADSs, the difference did not appear to be clinically meaningful. The malignancy rate among lesions classified as almost certainly benign was unexpectedly high at 1.9-2.3%, approximately double the expected rate of less than 1.0%.

Uterine artery embolization (UAE) is an effective uterine-preserving treatment for symptomatic uterine leiomyomas [1–3]. Postprocedure complications of UAE are typically acute, such as postembolization syndrome [4], pelvic infection [5], and expulsion of submucosal fibroids [1,6]. In this novel case, a patient presented 12 years after UAE with necrotic material filling the uterus ultimately requiring hysterectomy.

Objectives Transvaginal ultrasound is typically the initial diagnostic approach in patients with postmenopausal bleeding for detecting endometrial atypical hyperplasia/cancer. Although transvaginal ultrasound demonstrates notable sensitivity, its specificity remains limited. The objective of this study was to enhance the diagnostic accuracy of transvaginal ultrasound through the integration of artificial intelligence. By using transvaginal ultrasound images, we aimed to develop an artificial intelligence based automated segmentation model and an artificial intelligence based classifier model. Methods Patients with postmenopausal bleeding undergoing transvaginal ultrasound and endometrial sampling at Mayo Clinic between 2016 and 2021 were retrospectively included. Manual segmentation of images was performed by four physicians (readers). Patients were classified into cohort A (atypical hyperplasia/cancer) and cohort B (benign) based on the pathologic report of endometrial sampling. A fully automated segmentation model was developed, and the performance of the model in correctly identifying the endometrium was compared with physician made segmentation using similarity metrics. To develop the classifier model, radiomic features were calculated from the manually segmented regions-of-interest. These features were used to train a wide range of machine learning based classifiers. The top performing machine learning classifier was evaluated using a threefold approach, and diagnostic accuracy was assessed through the F1 score and area under the receiver operating characteristic curve (AUC-ROC). Results 302 patients were included. Automated segmentation-reader agreement was 0.790.21 using the Dice coefficient. For the classification task, 92 radiomic features related to pixel texture/shape/intensity were found to be significantly different between cohort A and B. The threefold evaluation of the top performing classifier model showed an AUC-ROC of 0.90 (range 0.88-0.92) on the validation set and 0.88 (range 0.86-0.91) on the hold-out test set. Sensitivity and specificity were 0.87 (range 0.77-0.94) and 0.86 (range 0.81-0.94), respectively. Conclusions We trained an artificial intelligence based algorithm to differentiate endometrial atypical hyperplasia/cancer from benign conditions on transvaginal ultrasound images in a population of patients with postmenopausal bleeding.

The Dobbs decision will directly affect patients and reproductive rights; it will also impact patients indirectly in many ways, one of which will be changes in the physician workforce through its impact on graduate medical education. Current residency accreditation standards require training in all forms of contraception in addition to training in the provision of abortion. State bans on abortions may diminish access to training as approximately half of obstetrics and gynecology residency programs are in states with significant abortion restrictions. The Dobbs decision creates numerous hurdles for trainees and their programs. Trainees in restrictive states will have to travel to learn in a different program in a protective state. As training opportunities diminish, potentially leading to a decline in clinical skills, knowledge, and experience in the provision of abortion, the rate of complications and maternal mortality are likely to rise. This will likely have a disproportionately negative effect on preexisting disparities in reproductive health fueled by a longstanding history of systemic racism and inequities. This work aims to both define the looming problem in abortion training created by Dobbs and propose solutions to ensure that an adequate workforce is available in the future to serve patient needs.

IntroductionIt is unclear whether ultrasound risk stratification models for adnexal lesions perform well when used by novice providers. We aim to compare the performance of four commonly used models to detect ovarian cancer, when the operator has only basic experience.MethodsWomen with adnexal masses treated in 2019 were identified retrospectively. Patients were included if they underwent surgery within 3 months of diagnosis or had at least 12±2 months of follow-up. A non-expert operator (European Federation of Societies for Ultrasound in Medicine and Biology level I) classified each lesion using ADNEX, two-step strategy (benign descriptors followed by ADNEX), O-RADS 2019, and O-RADS 2022. The primary outcome measure was AUC [95% confidence interval], compared across the four models.ResultsA total of 556 women were included in the analyses: 452 benign and 104 malignant. The AUCs of ADNEX, the two-step strategy, O-RADS 2019, and O-RADS 2022 were 0.90[0.87–0.94], 0.91[0.88–0.94], 0.88[0.85–0.91], and 0.88[0.84–0.91], respectively (figure 1). The two-step strategy performed significantly better than the O-RADS algorithms (both p=0.01). With all the algorithms, the observed malignancy rate was 1.91–2.17% among lesions categorized as ‘almost certainly benign’, two-fold higher than the expected <1% (table 1). Out of the four methods, lesions wrongly classified as ‘almost certainly benign’ were borderline tumors (n=4) and metastases (n=3).ConclusionsIn the hands of a novice provider, all algorithms performed well, and were able to distinguish benign from malignant lesions. ADNEX misclassified only one malignant patient as ‘almost certainly benign’, compared to 5–6 patients by the other models.

INTRODUCTION:The Fundamentals of Laparoscopic Surgery (FLS) program tests basic knowledge and skills required to perform laparoscopic surgery. Educational experiences in laparoscopic training and development of associated competencies have evolved since FLS inception, making it important to review the definition of fundamental laparoscopic skills. The Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) assigned an FLS Technical Skills Working Group to characterize technical skills used in basic laparoscopic surgery in current practice contexts and their possible application to future FLS tests.METHODS:A group of subject matter experts defined an inventory of 65 laparoscopic skills using a Nominal Group Technique. From these, a survey was developed rating these items for importance, frequency of use, and priority for testing for FLS certification. This survey was distributed to SAGES members, recent recipients of FLS certification, and members of the Association of Program Directors in Surgery (APDS). Results were collected using a secure web-based survey platform.RESULTS:Complete data were available for 1742 surveys. Of these, 1143 comprised results for post-residency participants who performed advanced procedures. Seventeen competencies were identified for FLS testing prioritization by determining the proportion of respondents who identified them of highest priority, at median (50th percentile) of the maximum survey scale rating. These included basic peritoneal access, laparoscope and instrument use, tissue manipulation, and specific problem management skills. Sixteen could be used to show appropriateness of the domain construct by confirmatory factor analysis. Of these 8 could be characterized as manipulative tasks. Of these 5 mapped to current FLS tasks.CONCLUSIONS:This survey-identified competencies, some of which are currently assessed in FLS, with a high level of priority for testing. Further work is needed to determine if this should prompt consideration of changes or additions to the FLS technical skills test component.

Introduction/Background Postmenopausal vaginal bleeding (PMB) is usually the first manifestation of endometrial cancer (EC) and endometrial atypical hyperplasia (EAH). Transvaginal ultrasound (TVUS) is often the first diagnostic step for PMB. Although TVUS has a high sensitivity, specificity is low and a high rate of invasive biopsy procedures are performed, the majority of which are found negative on pathologic evaluation. This study developed an Artificial Intelligence (AI) model based on TVUS images to improve the accuracy of TVUS in EAH/EC early recognition in patients with PMB. Methodology 300 patients with PMB were enrolled. All patients underwent TVUS and endometrial sampling within three months from TVUS. Manual segmentation of the endometrium on two static images for each patient was performed independently by two radiologists. Patients were classified into cohort A (EAH/EC) and cohort B (benign) based on the endometrial sampling report. A fully automated segmentation model (ASE) was developed. For the second phase, radiomic features were calculated from the regions-of-interest and individual feature analysis was evaluated. These features were also used to train a wide range of machine learning-based classifiers. Results ASE-reader agreement shows similar performance to inter-reader agreement (ASE-Reader agreement: Dice similarity of 0.79±0.21). For the classification task, the deep learning model identified 92 features related to image texture and pixel intensity that were significantly different between cohort A and B. The top performing classifier model was a Support Vector Classifier using Minimum Redundancy Maximum Relevance feature selection. For the 3-fold evaluation, the AUC was 0.90 [0.88–0.92] for validation, and 0.88 [0.86–0.91] on the hold-out test set. Conclusion We have trained an AI-based algorithm to differentiate EC/EAH from benign conditions based on TVUS images in a PMB population. Based on our preliminary results, we plan to expand this work in larger cohorts and evaluate the AI model in external datasets.

Systems of care have been established for obstetrics, trauma, and neonatology. An American College of Obstetricians and Gynecologists Presidential Task Force was established to develop a care system for gynecologic surgery. A group of experts who represent diverse perspectives in gynecologic practice proposed definitions of levels of gynecologic care using the Delphi method. The goal is to improve the quality of gynecologic surgical care performed in the United States by providing a framework of minimal institutional requirements for each level. Subgroups developed draft criteria for each level of care. The entire Task Force then met to reach consensus regarding the levels of care final definitions and parameters. The levels of gynecologic care framework focuses on systems of care by considering institutional resources and expertise, providing guidance on the provision of care in appropriate level facilities. These levels were defined by the ability to care for patients of increasing risk, complexity, and comorbidities, organizing gynecologic care around hospital capability. This framework can also be used to inform the escalation of care to appropriate facilities by identifying patients at risk and guiding them to facilities with the skills, expertise, and capabilities to safely and effectively meet their needs. The levels of gynecologic care framework is intended for use by patients, hospitals, and clinicians in the United States to guide where elective surgery can be done most safely and effectively by specialists and subspecialists in obstetrics and gynecology. The key features of the levels of gynecologic care include ensuring provision of risk-appropriate care and regionalization of care by facility capabilities.

OBJECTIVE: To examine the impact of access to and utilization of a commercially available question bank (True-Learn) for in-training examination (ITE) preparation in Obstetrics and Gynecology (OBGYN). DESIGN: This was a retrospective cohort study examining the impact of TrueLearn usage on ITE examination performance outcomes. Produced by the educational arm of the American College of Obstetricians and Gynecologists, the Council on Resident Education in Obstetrics and Gynecology (CREOG) exam is a multiple-choice test given to all residents annually. Residency programs participating in this study provided residency program mean CREOG scores from the year prior (2015), and the first (2016) and second (2017) years of TrueLearn usage. Programs also contributed resident-specific CREOG scores for each resident for 2016 and 2017. This data was combined with each resident's TrueLearn usage data that was provided by TrueLearn with residency program consent. The CREOG scores consisted of the CREOG score standardized to all program years, the CREOG score standardized to the same program year (PGY) and the total percent (%) correct. TrueLearn usage data included number of practice questions completed, number of practice tests taken, average number of days between successive tests, and percent correct of answered practice questions. SETTING: OBGYN Residency Training Programs. PARTICIPANTS: OBGYN residency programs that purchased and utilized TrueLearn for the 2016 CREOG examination were eligible for participation (n = 14). Ten residency programs participated, which consisted of 212 residents in 2016 and 218 residents in 2017. RESULTS: TrueLearn was used by 78.8% (167/212) of the residents in 2016 and 84.9% (185/218) of the residents in 2017. No significant difference was seen in the average CREOG scores available on a per- program level before versus after the first year of implementation either using the CREOG score standardized to all PGYs (mean difference 1.0; p = 0.58) or standardized to the same PGY (mean difference 3.1; p = 0.25). Using resident-level data, there was no significant difference in mean CREOG score standardized to all PGYs between users and non-users of TrueLearn in 2016 (mean, 199.4 vs 196.7; p = 0.41) or 2017 (mean, 198.2 vs 203.4; p = 0.19). The percent of practice questions answered correctly on TrueLearn was positively correlated with the CREOG score standardized to all PGYs (r = 0.47 for 2016 and r = 0.60 for 2017), as well as with the CREOG total percent correct (r = 0.47 for 2016 and r = 0.61 for 2017). Based on a simple linear regression, for every 500 practice questions completed, the CREOG score significantly increased for PGY-2 residents by an average (+/- SE) of 7.3 +/- 2.8 points (p = 0.013); the average increase was 0.7 +/- 2.5 (p = 0.79) for PGY-3 residents and 5.8 +/- 3.3 points (p = 0.09) for PGY-4 residents. CONCLUSIONS: Adoption of an online question bank did not result in higher mean CREOG scores at participating institutions. However, performance on the TrueLearn questions correlated with ITE performance, supporting predictive validity and the use of this question bank as a formative assessment for resident education and exam preparation. (C) 2022 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.