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Record W2593333189 · doi:10.1111/ctr.12956

Severe acute cellular rejection after intestinal transplantation is associated with poor patient and graft survival

2017· article· en· W2593333189 on OpenAlexaff
Geneviève Huard, Thomas D. Schiano, Jang Moon, Kishore Iyer

Bibliographic record

VenueClinical Transplantation · 2017
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineThymoglobulinTacrolimusMethylprednisoloneTransplantationRetrospective cohort studyInternal medicineSurgeryImmunosuppressionGastroenterology

Abstract

fetched live from OpenAlex

BACKGROUND: Severe acute cellular rejection (ACR) occurs frequently after intestinal transplantation (ITx). AIM: To evaluate the outcomes and the risk factors for graft failure and mortality in patients with severe ACR after ITx. METHODS: Retrospective study evaluating all ITx recipients who developed severe ACR between 01/2000 and 07/2014. Demographic and histologic data were reviewed. RESULTS: 20/126 (15.9%) ITx recipients developed severe ACR. Of these 20 episodes, 13 were in adults (median age: 47.1). The median (IQR) time from ITx to severe ACR was 206.5 (849) days. All patients received intravenous methylprednisolone and increased doses of tacrolimus. Sixteen (80%) patients did not respond to initial treatment and required thymoglobulin administration. Moreover, 11 (55%) patients required additional immunosuppressive medications. Six (30%) patients required graft enterectomy. Complications related to ACR treatment were the following: 10 (50%) patients developed bacterial infections, four (20%) patients developed cytomegalovirus infection and four (20%) patients developed post-transplant lymphoproliferative disease. At the end of follow-up, only 3/20 (15%) were alive with a functional allograft. The median patient survival time after diagnosis of severe ACR was 400 days (95% CI: 234.0-2613.0). CONCLUSIONS: Severe ACR episodes are associated with high rates of graft loss and complications related to treatment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.045
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

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

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 head0.034
GPT teacher head0.322
Teacher spread0.288 · 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 teacher head, 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

Citations20
Published2017
Admission routes1
Has abstractyes

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