医学
溃疡性结肠炎
结构效度
判别效度
疾病严重程度
内科学
内窥镜检查
疾病
可靠性(半导体)
收敛有效性
科克伦图书馆
物理疗法
荟萃分析
外科
患者满意度
内部一致性
功率(物理)
物理
量子力学
作者
Hadar Meringer,Maia Kayal,Vipul Jairath,Anila Qasim,John K MacDonald,Yuhong Yuan,Christopher Ma,Jean–Frédéric Colombel
标识
DOI:10.1093/ecco-jcc/jjaf126
摘要
BACKGROUND AND AIMS: Endoscopy is important for assessing disease severity and potentially predicting treatment response in acute severe ulcerative colitis (ASUC). We aimed to identify and determine the operating properties of existing endoscopic indices/items used to assess disease activity in ASUC. METHODS: MEDLINE, Embase, and Cochrane CENTRAL were searched from database inception to April 17, 2024 to identify individual items and scoring indices used to evaluate endoscopic disease activity in patients with ASUC. Subsequently, we performed another comprehensive search from database inception to July 29, 2024 to identify studies that assessed the validity, reliability, feasibility, and responsiveness of the identified items and scoring indices. RESULTS: We identified 18 studies that reported endoscopic measures in patients with ASUC, including Endoscopic Activity Index, Mayo endoscopic subscore (MES), Severe Endoscopic Lesions, Ulcerative Colitis Endoscopic Index of Severity (UCEIS), and the Degree of Ulcerative Colitis Burden of Luminal Inflammation (DUBLIN) score or sub-components of these indices. A total of 33 studies evaluated the operating properties of the MES, UCEIS, and DUBLIN score in ASUC. The MES and the UCEIS demonstrated adequate discriminant construct validity, convergent construct validity, and responsiveness. Feasibility or reliability were not assessed for these scores. The DUBLIN score demonstrated indeterminate discriminant construct validity and convergent construct validity with limited data. Responsiveness, feasibility, and reliability were not assessed for this score. CONCLUSIONS: These results highlight the need for a validated endoscopic score that can accurately describe and quantify the severity of endoscopic lesions and potentially predict outcomes in ASUC patients.
科研通智能强力驱动
Strongly Powered by AbleSci AI