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Updated: Jul 23, 2025

Systematic Scoring Analysis for Intestinal Inflammation in a Murine Dextran Sodium Sulfate-Induced Colitis Model
Published on: February 14, 2021
Propensity score analysis the clinical characteristics of active distal and extensive ulcerative colitis: a
Changchang Ge1, Zhaofeng Shen1, Yi Lu1
1Jiangsu Provincial Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Abstract:
Background and Objectives: Ulcerative Colitis (UC) subtypes defined by disease extent and shared pathophysiology are important. Analyzing the clinical characteristics of UC with different disease extent and optimizing clinical typing are conducive to the pathogenesis research, disease monitoring and precise treatment. Methods: 188 patients with active UC were divided into distal and extensive colitis. The clinical characteristics of the two groups were analyzed by propensity score. Spearman is used for correlation analysis, and receiver operating characteristic (ROC) curve was used to evaluate the ability of clinical indicators to predict Mayo endoscopic subscore (MES). Results: Compared with distal colitis, extensive colitis had more severe disease activity, younger age, higher utilization rate of corticosteroids and incidence of extra intestinal manifestations (EIMs), and clinical indicators were differentially expressed in the two groups. After using propensity score, the incidence of EIMs in the extensive colitis was still higher than that in distal colitis. Inflammation, coagulation and immune indicators like CRP, FC, IL-10, D-D and α1-MG are higher in extensive colitis, and metabolic indicators like LDL-C, HDL-C, TC, GSP and albumin are higher in distal colitis. The correlation between clinical indicators and MES is affected by disease extent. The area under curve (AUC) of CRP + D-D + α2-MG for predicting distal colitis MES3 was 0.85, and the AUC of IL-6+ GSP+ α1-MG predicted extensive colitis MES3 can reach 0.82. Conclusion: Differential clinical indicators can become potential markers for predicting disease progression and prognosis, and have significance for UC mechanism research and drug development. We can select biomarkers according to lesion site.
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