Transgender and gender diverse (TGD) people with endometriosis have unique health needs. Current health research, policy, and clinical practice are developed within a biomedical and cisheteronormative paradigm that structurally excludes …
The pharmacological treatment of endometriosis using SPRMs requires improvement. The pure PR-agonist dienogest (DNG), a clinically established progestin, can serve as a reference compound for comparison. Its efficacy and safety …
This study aimed (i) to examine symptom burden, health care use, perceived treatment effectiveness and experiences of trivialization among women with chronic pelvic pain (CPP), and (ii) to identify predictors …
Orofacial pain (OFP) is a multidimensional clinical problem that includes conditions such as temporomandibular disorders (TMD). It is often associated with chronic overlapping pain conditions (COPCs), including gastrointestinal, gynecological and …
Deep endometriosis affecting the lateral pelvic structures (LPS) is a complex and often underdiagnosed manifestation of the disease. The authors review the anatomic features of the LPS and underscore the …
Endometriosis is frequently associated with infertility and postoperative recurrence, and fertility-sparing surgery may be considered when symptoms, endometriomas, adhesions, or deep infiltrating disease are unlikely to be adequately managed with …
Assisted reproductive technology (ART) is increasingly utilized worldwide, yet concerns remain regarding its potential association with breast and gynecological malignancies and the safety of fertility-preservation strategies in cancer survivors. Ovarian …
Implantation failure remains a major challenge in assisted reproductive technology (ART) and is a significant contributor to infertility in women with endometriosis. Beyond mechanical distortion and ovarian dysfunction, increasing evidence …
Endometriosis is a common gynecological disorder that requires accurate detection of ectopic lesions in laparoscopic images for effective diagnosis and treatment. However, existing deep learning-based detection methods face significant challenges …