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Developing a novel risk-scoring system for predicting relapse in patients with ulcerative colitis: A prospective cohort study

OBJECTIVES: Ulcerative Colitis (UC) follows a natural clinical course of relapses and remissions. The aim of this study was to construct a risk-scoring formula in order to enable predicting relapses in patients with UC. METHODS: From October 2012 to October 2013, 157 patients from Shiraz, southern I...

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Autores principales: Hosseini, Seyed Vahid, Safarpour, Ali Reza, Taghavi, Seyed Alireza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Professional Medical Publications 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4744311/
https://www.ncbi.nlm.nih.gov/pubmed/26870126
http://dx.doi.org/10.12669/pjms.316.8811
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author Hosseini, Seyed Vahid
Safarpour, Ali Reza
Taghavi, Seyed Alireza
author_facet Hosseini, Seyed Vahid
Safarpour, Ali Reza
Taghavi, Seyed Alireza
author_sort Hosseini, Seyed Vahid
collection PubMed
description OBJECTIVES: Ulcerative Colitis (UC) follows a natural clinical course of relapses and remissions. The aim of this study was to construct a risk-scoring formula in order to enable predicting relapses in patients with UC. METHODS: From October 2012 to October 2013, 157 patients from Shiraz, southern Iran who were diagnosed with UC and in remission were enrolled. At 3-month intervals, multiple risk factors of hemoglobin, complete blood counts, serum iron and albumin, erythrocyte sedimentation rate, and faecal calprotectin levels, sex, age, cigarette smoking, positive family history of inflammatory bowel diseases, past history of appendectomy, extra-intestinal accompanying diseases, extent of disease at the beginning of study, number of previous relapses, duration of disease and duration of remission before the study were assessed. Univariate and multivariate logistic regression were applied to fit the final model. The new risk-scoring system accuracy was assessed using receiver-operating-characteristics (ROC) curve analysis. RESULTS: Seventy four patients (48.1%) experienced a relapse. Multivariate analysis revealed that relapses could significantly be predicted by the level of fecal calprotectin (OR=8.1), age (OR=9.2), the Seo activity index (OR=52.7), and the number of previous relapses (OR=4.2). The risk scoring formula was developed using the regression coefficient values of the aforementioned variables. CONCLUSION: Four predictor variables were significant in the final model and were used in our risk-scoring formula. It is recommended that patients who achieve high scores are diligently observed, treated, and followed up.
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spelling pubmed-47443112016-02-11 Developing a novel risk-scoring system for predicting relapse in patients with ulcerative colitis: A prospective cohort study Hosseini, Seyed Vahid Safarpour, Ali Reza Taghavi, Seyed Alireza Pak J Med Sci Original Article OBJECTIVES: Ulcerative Colitis (UC) follows a natural clinical course of relapses and remissions. The aim of this study was to construct a risk-scoring formula in order to enable predicting relapses in patients with UC. METHODS: From October 2012 to October 2013, 157 patients from Shiraz, southern Iran who were diagnosed with UC and in remission were enrolled. At 3-month intervals, multiple risk factors of hemoglobin, complete blood counts, serum iron and albumin, erythrocyte sedimentation rate, and faecal calprotectin levels, sex, age, cigarette smoking, positive family history of inflammatory bowel diseases, past history of appendectomy, extra-intestinal accompanying diseases, extent of disease at the beginning of study, number of previous relapses, duration of disease and duration of remission before the study were assessed. Univariate and multivariate logistic regression were applied to fit the final model. The new risk-scoring system accuracy was assessed using receiver-operating-characteristics (ROC) curve analysis. RESULTS: Seventy four patients (48.1%) experienced a relapse. Multivariate analysis revealed that relapses could significantly be predicted by the level of fecal calprotectin (OR=8.1), age (OR=9.2), the Seo activity index (OR=52.7), and the number of previous relapses (OR=4.2). The risk scoring formula was developed using the regression coefficient values of the aforementioned variables. CONCLUSION: Four predictor variables were significant in the final model and were used in our risk-scoring formula. It is recommended that patients who achieve high scores are diligently observed, treated, and followed up. Professional Medical Publications 2015 /pmc/articles/PMC4744311/ /pubmed/26870126 http://dx.doi.org/10.12669/pjms.316.8811 Text en Copyright: © Pakistan Journal of Medical Sciences http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Hosseini, Seyed Vahid
Safarpour, Ali Reza
Taghavi, Seyed Alireza
Developing a novel risk-scoring system for predicting relapse in patients with ulcerative colitis: A prospective cohort study
title Developing a novel risk-scoring system for predicting relapse in patients with ulcerative colitis: A prospective cohort study
title_full Developing a novel risk-scoring system for predicting relapse in patients with ulcerative colitis: A prospective cohort study
title_fullStr Developing a novel risk-scoring system for predicting relapse in patients with ulcerative colitis: A prospective cohort study
title_full_unstemmed Developing a novel risk-scoring system for predicting relapse in patients with ulcerative colitis: A prospective cohort study
title_short Developing a novel risk-scoring system for predicting relapse in patients with ulcerative colitis: A prospective cohort study
title_sort developing a novel risk-scoring system for predicting relapse in patients with ulcerative colitis: a prospective cohort study
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4744311/
https://www.ncbi.nlm.nih.gov/pubmed/26870126
http://dx.doi.org/10.12669/pjms.316.8811
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