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Record W4251295766 · doi:10.1093/ecco-jcc/jjw019.438

P319. Combining anti-inflammatory treatment with antiviral treatment in severe cytomegalovirus-positive ulcerative colitis does not affect colectomy rate: a retrospective European multicentre study

2016· article· en· W4251295766 on OpenAlexaff
Yutaka Nagata, Motohiro Esaki, Atsushi Hirano, Junji Umeno, Yuji Maehata, Takehiro Torisu, Taiki Moriyama, Takayuki Matsumoto, Takanari Kitazono, Uri Kopylov, K. Papamichael, Konstantinos H. Katsanos, Matti Waterman, A Bar-, Gil Shitrit, Trine Boysen, Francisco Portela, Armando Peixoto, Andrew Szilagyi, M Silva, Giovanni Maconi, Ofir Har‐Noy, Peter Bossuyt, Gerasimos Mantzaris, M Barreiro De Acosta, María Chaparro, Dimitrios Christodoulou, Rami Eliakim, Jean‐François Rahier, Fernando Magro, Shomron Ben‐Horin, Xavier Roblin

Bibliographic record

VenueJournal of Crohn s and Colitis · 2016
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsUlcerative colitisMedicineColectomyGastroenterologyAntiviral treatmentInternal medicineCytomegalovirusAffect (linguistics)Total ColectomyRetrospective cohort studyCytomegalovirus infectionVirusImmunologyHuman cytomegalovirusHerpesviridaeViral diseaseDiseaseChronic hepatitis

Abstract

fetched live from OpenAlex

Background: In patients with Crohn's disease (CD), intestinal complications requiring intestinal surgery occur during their clinical course.Although preventive effect of anti-tumour necrosis factor alpha (anti-TNF) therapy against postoperative recurrence in CD has been well discussed, its preventive effect against initial intestinal resection (IIR) remains uncertain.We aimed to investigate whether anti-TNF therapy decreases the risk of IIR after the diagnosis of CD.Methods: We retrospectively investigated clinical course of 247 patients who were diagnosed as CD at our institution during 1973-2014.Amongst them, 14 patients who required IIR within a 1 year, and 30 patients who were primarily nonresponsive or intolerant to anti-TNF therapy were excluded from the analysis.The remaining 203 subjects were then classified into TNF and non-TNF groups, according to the use of anti-TNF therapy during their clinical course.Clinical characteristics and medical treatments other than anti-TNF therapy were compared between the 2 groups.With the multivariate analysis using Cox proportional hazard model, the risk of IIR was compared between TNF group and non-TNF group.We further assessed the effect of anti-TNF therapy against IIR amongst 100 patients with inflammatory CD.Results: There were 89 patients in the TNF group and 114 patients in the non-TNF group.Colitis type (19% vs 9%; p = 0.034) and inflammatory CD (71% vs 33%; p < 0.0001) were more frequent in the TNF group than in the non-TNF group, whereas previous history of intestinal resection before the diagnosis (15% vs 30%; p = 0.012) was less frequent in the TNF group.As for medical treatments, immunosuppressant was more frequently applied in the TNF group than in the non-TNF group (43% vs 25%; p = 0.011), whereas nutritional therapy of elemental diet or low residue diet was more frequently used in the latter than in the former (76% vs 60%; p = 0.014).During a mean of 91 months follow-up period, 74 patients required IIR.Multivariate analysis demonstrated that anti-TNF therapy was a significant factor associated with the decrease in the risk of IIR (hazard ratio) [HR]; 0.361, 95% confidence interval [CI]; 0.176-0.688).In 100 patients with inflammatory CD, anti-TNF therapy was a significant factor associated with the decrease in the risk (HR; 0.313, 95%CI; 0.084-0.985).Conclusions: Anti-TNF therapy may contribute to the reduction in the risk of intestinal resection after the initial diagnosis of CD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.285
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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