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Record W2270444836 · doi:10.1186/s40842-016-0019-7

Tacrolimus toxicity in islet transplantation due to interaction with macrolides

2016· article· en· W2270444836 on OpenAlexaff
Kitty Kit-Ting Cheung, Peter Senior

Bibliographic record

VenueClinical Diabetes and Endocrinology · 2016
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of AlbertaCapital District Health Authority
Fundersnot available
KeywordsTacrolimusMedicineNephrotoxicityTransplantationNeurotoxicityToxicityClarithromycinPharmacologyProtein synthesis inhibitorAntibioticsIntensive care medicineAntibacterial agentSurgeryInternal medicineChemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Drug interactions are an important risk in transplant patients. Case presentation: This case describes an incident where a patient with islet transplantation, who was using tacrolimus as part of the immunosuppressant regime, was started on a course of clarithromycin and experienced nephrotoxicity and neurotoxicity. He was an outpatient at that time and was managed with temporary cessation of tacrolimus until the tacrolimus level returned to target and his symptoms resolved. He recovered well and was resumed on his usual dosage of tacrolimus to prevent rejection of islets. CONCLUSION: Care should be taken with commonly used antibiotics to avoid potentially dangerous interactions with immunosuppressant drugs.

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 score0.073
Threshold uncertainty score0.255

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 head0.352
Teacher spread0.318 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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