To evaluate the clinical impact of incorporating patient specific 3-dimensional (3D) printed anatomical models into gynecological practice for improving surgical planning and patient outcomes in patients with deep endometriosis.
Ovarian endometriomas are commonly assessed according to cyst size and laterality, anatomical features that have long been regarded as indicators of disease severity and potential ovarian compromise. Consequently, these characteristics …
Plastics are ubiquitous in the environment and are widely used in food packaging, medicine, agriculture, construction and other sectors. However, the plasticizers they contain pose a substantial threat to environmental …
Decidualized ovarian endometriomas are benign lesions that can closely mimic ovarian malignancy on ultrasound. Correctly identifying them is crucial to avoid unnecessary interventions and associated adverse fetal-maternal outcomes. A systematic …
Since the complications associated with endometriosis during pregnancy are rare, there is not enough evidence to indicate that this disease has major detrimental effects on pregnancy outcome. Therefore, the present …
To evaluate how the AAGL 2021, #Enzian, and revised American Society for Reproductive Medicine (rASRM) classifications reflect operative time, advanced surgical procedures, and blood-loss-related perioperative outcomes in a video-reassessed cohort …
Uterine corpus endometrial carcinoma (UCEC) ranks as the 6th most common malignancy among women. Emerging evidence indicates that the dysregulation of tRNA-derived fragments (tRFs) is involved in the pathogenesis of …
To evaluate whether preoperative clinical Enzian scoring and digital rectal examination improve accuracy of operative time prediction and surgical outcomes in women undergoing surgery for endometriosis.
This study aimed to investigate whether women with unilateral and bilateral OMA differ in anxiety symptoms, and secondarily in depressive symptoms and sexual dysfunction symptoms, and to evaluate the independent …
To apply an MR-PheWAS to infer causality between NSW and multiple health outcomes.