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Sirolimus‐Induced Ulceration of the Small Bowel in Islet Transplant Recipients: Report of Two Cases

2005· article· en· W2112601668 on OpenAlexaff
Michele Molinari, Faisal Alsaif, Edmond A. Ryan, Jonathan R.T. Lakey, Peter Senior, Breay W. Paty, David L. Bigam, Norman M. Kneteman, A. M. James Shapiro

Bibliographic record

VenueAmerican Journal of Transplantation · 2005
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineSirolimusImmunosuppressionTacrolimusGastroenterologyTransplantationAdverse effectCalcineurinNephrotoxicityDiabetes mellitusInternal medicineKidney transplantationRegimenMucositisAbdominal painSurgeryKidneyToxicityEndocrinology

Abstract

fetched live from OpenAlex

Sirolimus (SRL) has been used for most islet recipients over the past 5 years. It provides balanced immunosuppression in combination with low-dose calcineurin inhibitors, while avoiding corticosteroids. This regimen decreases the risk of nephrotoxicity, neurotoxicity and diabetogenicity. SRL has also been used selectively in clinical liver and kidney transplantation. A number of common side effects including anemia, leucopenia, thrombocytopenia, hypercholesterolemia, mouth ulceration, joint pain, extremity edema and impaired wound healing have been associated with the use of SRL. As SRL is used more frequently, evidence has been gathered on its rare but severe side effects. We report 2 patients who underwent islet transplantation and developed symptomatic small bowel ulceration that resolved after complete withdrawal of SRL. Although small bowel ulceration is rare, it can potentially progress to more serious complications if not treated adequately. Our experience highlights an uncommon but potentially serious adverse effect of high-dose SRL in islet recipients.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.279
Teacher spread0.260 · 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 designCase report
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

Citations57
Published2005
Admission routes1
Has abstractno

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