ArticleJournal of inflammation research2022
Predicting Mucosal Healing in Crohn's Disease: A Nomogram Model Developed from a Retrospective Cohort.
Article in Journal of inflammation research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mucosal and Transmural Healing and Long-term Outcomes in Crohn's Disease.Inflammatory bowel diseases · 2025Pooled it
- Development and validation of the SYSU-score for MRI-based transmural healing assessment in Crohn's disease: a dual-center study.European radiology · 2026Article
- Risk Factors for Carbapenem Resistant Gram Negative Bacteria (CR-GNB) Carriage Upon Admission to the Gastroenterology Department in a Tertiary First Class Hospital of China: Development and Assessment of a New Predictive Nomogram.Infection and drug resistance · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Mucosal healing (MH) has become a therapeutic end point for Crohn's disease (CD). The purpose of this study was to identify potential risk factors responsible for a lower probability of mucosal healing in CD. It also aimed to create and validate a noninvasive tool for predicting mucosal healing in CD to aid clinical decision-making. Patients and Methods: We established a derivation cohort diagnosed with CD, in which endoscopic examination was performed before and after treatment at the First Affiliated Hospital of Nanjing Medical University between January 2010 and June 2021. Patient data including demographic and clinical characteristics and treatment details were collected. The achievement of mucosal healing (without ulceration on endoscopic examination) after treatment was the endpoint observed during follow-up. We performed logistic regression analysis to identify factors associated with mucosal healing. These factors were used to develop a model (CD mucosal healing prediction nomogram) to predict mucosal healing in CD. External validation was performed using a new cohort of 60 patients from the Second Affiliated Hospital of Soochow University between January 2012 and June 2021. Results: A total of 331 patients were included in the derivation cohort. We found the following factors to be independently associated with mucosal healing after treatment: disease course <11 months, ulcer size <0.5 cm, Harvey-Bradshaw Index score <9, infliximab treatment, and non-exclusive use of 5-aminosalicylic acid. The model incorporating these factors achieved good discrimination, calibration, and clinical decision curve analysis results on internal validation (C-index: 0.788, 95% confidence interval [CI]: 0.74-0.84). The external validation cohort also demonstrated good discrimination (C-index: 0.785, 95% CI: 0.68-0.90) and calibration. Conclusion: The CD mucosal healing prediction nomogram model demonstrated good reliability and validated. It can potentially be developed into a simple and clinically useful tool for predicting mucosal healing in CD.
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