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Record W2126375823 · doi:10.1183/09031936.00026107

Azathioprine and diffuse alveolar haemorrhage: the pharmacogenetics of thiopurine methyltransferase

2007· article· en· W2126375823 on OpenAlexaff
Davide Perri, Diane E. Cole, Orrie M. Friedman, Eugenia Piliotis, S. Mintz, Nimesh Adhikari

Bibliographic record

VenueEuropean Respiratory Journal · 2007
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsThiopurine methyltransferaseAzathioprineMedicineLeukopeniaPharmacogeneticsDosingGastroenterologyMethyltransferaseBone marrow suppressionInternal medicineToxicityGenotypeBiologyDiseaseGenetics

Abstract

fetched live from OpenAlex

Current guidelines support the use of corticosteroids and azathioprine as one possible treatment strategy for idiopathic pulmonary fibrosis (IPF). However, some patients with genetic polymorphisms of thiopurine methyltransferase (TPMT) are at risk of severe azathioprine myelotoxicity. The current authors present the case of an 85-yr-old Caucasian male with IPF who developed diffuse alveolar haemorrhage as a complication of azathioprine-induced myelosuppression. Leukocyte genetic TPMT testing revealed that the patient had homozygous polymorphisms associated with the absence of TPMT activity and severe azathioprine-induced myelotoxicity. Thiopurine methyltransferase deficiency should be considered in patients who develop leukopenia early in treatment with azathiopurine, or who present with severe marrow suppression at usual doses. For centres with equipped laboratories, a dosing suggestion is provided based on thiopurine methyltransferase testing. Even with screening strategies, frequent monitoring of complete blood count and liver biochemistry should remain the mainstay of surveillance for azathioprine toxicity.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.310
Teacher spread0.283 · 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

Citations22
Published2007
Admission routes1
Has abstractyes

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