OP07.07: Utilising transvaginal endometriosis ultrasound to triage endometriosis surgical cases to either a district hospital versus a tertiary hospital

Transvaginal ultrasound is highly effective for diagnosing gynecological conditions like deep endometriosis, uterine pathologies, and evaluating adnexal masses. This study aims to emphasise the role of transvaginal ultrasound in directing surgical cases to suitable hospital levels and fostering the advancement of surgical proficiency among trainees. A retrospective analysis of gynecological interventions was carried out by the Endometriosis Ultrasound and Advanced Endosurgery Unit at Nepean Hospital. Preoperative assessments involved the utilisation of Transvaginal Endometriosis Ultrasound (TVES) by the unit. Patients were allocated for treatment either to a tertiary hospital with a multidisciplinary team or to a district hospital based on the complexity of their diagnostic outcomes. This method ensured suitable case selection for trainees and fellows. Over a span of six years, 1,682 elective gynecological procedures were conducted, with 30.97% identified as complex cases. Among these, 70.1% were diagnosed or suspected with endometriosis via TVES. Additionally, 61.9% were suitable for treatment at the district hospital, while 38.1% required a multidisciplinary surgical approach at the tertiary hospital due to their advanced classification (UBESS III). Only 1.64% of cases required further surgical intervention at the tertiary hospital due to incomplete resection or higher complexity. Notably, TVES exhibited higher specificity in detecting endometriosis, demonstrating superior accuracy (87% vs. 72%) for deep compared to superficial cases. Preoperative strategizing represents a fundamental preprocedural step aimed at risk mitigation and the attainment of favourable surgical outcomes. Within the framework of surgical planning, TVES has demonstrated efficacy as a proficient stratification tool, particularly beneficial for training purposes. It serves to adeptly allocate cases based on their complexity, thereby enhancing the educational experience for trainees.