12221 External Validation Study of Pre-Operative Ultrasound Based AAGL Staging System (AAGL-US) in Prediction of AAGL Surgical Stage
Year: 2024
Type: article
Study design: Observational Study
Abstract: Study Objective To externally validate the AAGL-US in prediction of AAGL surgical stage following on from previously published data in 2022. Design Retrospective multicentre observational study. Setting Recruited through gynaecology ultrasound and endometriosis surgery outpatient clinic and operated by experienced laparoscopists. Patients or Participants Patients recruited from August 2018-November 2019 that presented for investigation and management of possible endometriosis with data presented previously in separate analysis. Patients were over 18 years of age. Excluded if post menopausal, diagnosis of malignancy, pregnant or unable to undergo trans-vaginal ultrasound. Interventions Patients underwent a deep endometriosis ultrasound conducted in accordance with the IDEA consensus prior to surgical assessment and management. AAGL-US stage (1-4) was documented retrospectively while surgical stage (AAGL 1-4) was assessed contemporaneously based on findings at time of surgery. Measurements and Main Results A total of 236 patients were included in the analysis. The weighted kappa score of the performance of AAGL-US in prediction of the AAGL surgical stage was 0.5 demonstrating moderate agreement. Intraclass correlation was highest as good reliability for right ovary, left ovary, bladder and rectum with ICC scores of 0.83, 0.84, 0.80 and 0.76 respectively. Pouch of Douglass obliteration demonstrated moderate reliability at 0.53. Diagnostic accuracy in AAGL-U in prediction of presence of any endometriosis showed sensitivity 0.56, specificity 0.60, positive predictive value 0.97, negative predictive value 0.23. Conclusion There is moderate agreement between AAGL-US and AALG surgical stage with weighted kappa 0.50 much lower than previously reported 0.76. ICC was similar in assessment of ovaries, bladder and recal disease to previously reported data.
Language: English
Subfield: Reproductive Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,000
OpenAlex ID: W4404350640
