Mucosal Healing Predicts the Long-Term Prognosis of Intestinal Behçet’s Disease View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-10

AUTHORS

Sun Mie Yim, Duk Hwan Kim, Hyun Jung Lee, Hui Won Jang, Soo Jung Park, Sung Pil Hong, Tae Il Kim, Won Ho Kim, Jae Hee Cheon

ABSTRACT

BACKGROUND: Mucosal healing (MH) has emerged as a therapeutic goal in the treatment of inflammatory bowel disease; however, little is known about the impact of MH on the prognosis of intestinal Behçet's disease (BD). AIM: We investigated whether MH could predict the prognosis of intestinal BD. METHODS: We retrospectively reviewed the medical records of 80 patients with intestinal BD who underwent colonoscopy within 3 months after clinical remission. The clinical recurrence rate according to the presence or absence of MH was evaluated using the Kaplan-Meier method and the log-rank test. In order to evaluate MH as an independent prognostic factor, a multivariate analysis using Cox proportional hazards regression model was performed including other potential factors for the relapse of intestinal BD. RESULTS: The number of patients with active ulcers at the time of clinical remission was 57 (71.3%), while 23 patients (28.7%) were experiencing MH. In the active ulcer group, 39 patients (68.4%) experienced recurrence during the follow-up period, whereas 7 patients (30.4%) recurred in the MH group. The cumulative recurrence rate was significantly higher in the active ulcer group than in the MH group (P < 0.001). A multivariate analysis identified active ulcers at the time of clinical remission as an independent predictive factor for relapse. CONCLUSION: Our study demonstrates that MH is an independent factor predictive of long-term prognosis of intestinal BD. MH might be the ultimate therapeutic goal in the treatment of intestinal BD. More... »

PAGES

2529-2535

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10620-014-3198-z

DOI

http://dx.doi.org/10.1007/s10620-014-3198-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1024774507

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24838499


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10620-014-3198-z'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10620-014-3198-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10620-014-3198-z'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10620-014-3198-z'


 

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