Visual-Numeric Endometriosis Scoring System (VNESS) for mapping surgical findings: A validation study.
S Khazali, B Mondelli, K Fleischer, A Bachi, M Adamczyk, N Lemos, H Krentel, A Vashisht, A Abdalla, A Mohazzab, G Delanerolle, M Possover, R Padmehr, K Shadjoo, G Moawad, T Lee, E Saridogan
Background: Several endometriosis classification systems have been proposed and published but the search for a universal language that communicates the complexity, laterality and severity of this disease continues. The authors introduce the Visual-Numeric Endometriosis Scoring System. VNESS is a novel system for describing surgical findings in each compartment of the pelvis in a way that is simple to use, visually intuitive and mirrors a laparoscopic image of the pelvis. Objective: The aim of this study was to assess inter-rater reliability for components of VNESS. Materials and Methods: The project took the format of a validation study using short surgical laparoscopic video clips. Anonymised video clips of endometriosis procedures were scored by 50 Gynaecologists of varying levels of experience from 12 different countries. The clips were collated from a series of procedures performed between 2012 and 2022. Each participant scored 93 short surgical clips using VNESS. 4650 scores were compared against a reference score and analysis was performed to assess inter-rater reliability. Main outcome measures: The outcome measures were percentage agreement between given and reference scores, as well as intra-class correlation coefficients (ICC), Cohen Kappa and Quadratic Weighted Kappa Coefficients calculated to evaluate inter-rater reliability. Results: The highest and lowest percentage agreement with the reference score was seen in VNESS 4 (full thickness disease, 97% perfect agreement) and VNESS 1 (superficial disease, 53% perfect agreement) respectively. The intraclass correlation coefficient showed strong inter-rater reliability for all VNESS compartments except the vagina. Conclusions: This study suggests that VNESS has excellent reliability between observers. Correlation is stronger with more severe disease.
