Clinical obstetrics and gynecology最新文献

What was done? A review of artificial intelligence (AI) applications for the imaging of uterine fibroids, endometriosis, and adenomyosis. What was found? AI models can assist with the recognition, segmentation, and localization of uterine fibroids, and the differentiation of benign fibroids and sarcomas. Models can aid in the diagnosis of adenomyosis and endometriosis, and the prediction of the impact of endometriosis on fertility. What the findings mean? Deployed thoughtfully, AI tools could reduce variability, shorten read times, and add objective measurements to routine care. Studies evaluating these models are limited by single-institution designs and continued reliance on expert sonologists and radiologists.

Hereditary cancer syndromes are associated with up to 25% of ovarian and 5% of endometrial cancers, yet rates of genetic testing and counseling remain low. Artificial intelligence (AI) offers new opportunities to streamline risk assessment, enhance gene variant interpretation, and expand access to genetic counseling. This narrative review synthesizes current evidence on AI applications in gynecologic cancer genetic risk assessment, including chatbot-based risk assessment, natural language processing of electronic records, and machine-learning approaches to variant classification. We highlight key challenges, including data bias, privacy, and implementation barriers, and outline future directions for AI technologies in gynecologic cancer genetic risk assessment.

Artificial intelligence is transforming healthcare, including obstetrics and gynecology, with applications for diagnostics, outcome prediction, and clinical decision support. Gynecologic surgery has begun to utilize machine learning to harness the massive datasets generated by minimally invasive gynecologic procedures to objectively assess surgical skill, enhance preoperative planning, improve intraoperative anatomy recognition, and, most importantly, correlate surgical technique with patient outcomes. This narrative review summarizes the current state of artificial intelligence in gynecologic surgery, the challenges and limitations its application faces within the field, and possible future advances within gynecologic surgical care and patient safety.

The vulvar dermatologic examination is a crucial component of gynecologic and dermatologic practice, requiring a thorough understanding of normal anatomy and physiologic variations, and common pathologic conditions. This review outlines key elements of the history-taking process, including demographic factors, symptoms, product use, and relevant medical history, which help guide diagnostic evaluation. A structured approach to distinguishing normal anatomic variations from disease is emphasized, including the identification of physiological changes across the lifespan and common benign lesions that may mimic pathology. Proper vulvar hygiene and personal care habits play a significant role in maintaining vulvar health and preventing irritant or allergic reactions. We review evidence-based recommendations on cleansing practices, product selection, and environmental factors that contribute to vulvar irritation, as well as common allergens and irritants implicated in contact dermatitis. In addition, we discuss the indications for vulvar biopsy, emphasizing its role in distinguishing benign inflammatory conditions from premalignant or malignant processes. Specific biopsy techniques and procedural considerations are highlighted to ensure accurate histopathologic diagnosis and optimal patient outcomes. This guide provides clinicians with a practical framework for evaluating the vulva, integrating history-taking, physical examination, patient education, and diagnostic interventions to improve care for individuals presenting with vulvar complaints.

Patients with disabilities face significant disparities in preventive gynecologic care due to systemic barriers, limited provider training, and pervasive bias. These challenges contribute to reduced uptake of HPV vaccination, cervical and breast cancer screening, resulting in higher rates of late-stage diagnoses and mortality. Gynecologic clinicians play a critical role in addressing these inequities by fostering autonomy-centered communication, providing appropriate accommodations, and adhering to evidence-based screening guidelines. This review summarizes key practices to enhance preventive care for patients with disabilities and highlights areas of needed improvement in clinical training, clinical environments, and access to cancer prevention services.

Despite representing one of the largest and fastest-growing subpopulations of reproductive-age women, women with disabilities experience profound disparities in sexual and reproductive health care. Women with disabilities face disproportionately high rates of unmet sexual health needs, inadequate sexual education, and elevated risks of sexual abuse and intimate partner violence (IPV). These inequities are driven by structural, interpersonal, and clinical barriers that remain poorly addressed within women's health care systems. Given the importance of addressing reproductive health care needs, it is crucial that clinicians understand the needs of women with disabilities, implement disability-competent communication strategies, and ensure trauma-informed, accessible care.

Over the past few decades, the prevalence of diabetes in pregnancy has increased significantly necessitating innovative methods to optimize care for patients. Group prenatal care has emerged as a promising model in response to rising health care costs and declining patient satisfaction with traditional care approaches. Although traditionally used for low-risk patients, group prenatal care has expanded to pregnant patients with diabetes. The role of technology for diabetes in pregnancy has also expanded to include continuous glucose monitors, electronic data repositories, and remote glycemic monitoring. This review aims to examine existing literature on innovative prenatal care in the context of diabetes.