Khazali S, Mondelli B, Fleischer K, Bachi A, Adamczyk M, Lemos N, Krentel H, Vashisht A, Abdalla A, Mohazzab A, Delanerolle G, Possover M, Padmehr R, Shadjoo K, Moawad G, Lee T, Saridogan E
Facts Views Vis Obgyn. 2024 Dec;16(4):429-439. doi: 10.52054/FVVO.16.4.051.
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.
The aim of this study was to assess inter-rater reliability for components of VNESS.
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.
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.
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.
This study suggests that VNESS has excellent reliability between observers. Correlation is stronger with more severe disease.
已经提出并发表了几种子宫内膜异位症分类系统，但寻找一种能够传达该疾病的复杂性、双侧性和严重程度的通用语言的工作仍在继续。作者介绍了视觉数字子宫内膜异位症评分系统（VNESS）。VNESS是一种新颖的系统，用于以简单易用、视觉直观且能反映骨盆腹腔镜图像的方式描述骨盆各腔室的手术发现。
本研究的目的是评估VNESS各组成部分的评分者间信度。
该项目采用使用简短腹腔镜手术视频片段的验证研究形式。来自12个不同国家的50名经验水平各异的妇科医生对匿名的子宫内膜异位症手术视频片段进行评分。这些片段来自2012年至2022年期间进行的一系列手术。每位参与者使用VNESS对93个简短手术片段进行评分。将4650个评分与参考评分进行比较，并进行分析以评估评分者间信度。
观察指标为给定评分与参考评分之间的百分比一致性，以及计算得出的组内相关系数（ICC）、科恩kappa系数和二次加权kappa系数，以评估评分者间信度。
与参考评分的最高和最低百分比一致性分别出现在VNESS 4（全层疾病，97%完全一致）和VNESS 1（浅表疾病，53%完全一致）中。组内相关系数显示，除阴道外，所有VNESS腔室的评分者间信度都很强。
本研究表明VNESS在观察者之间具有出色的信度。疾病越严重，相关性越强。
