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Record W2426687844

The effect of ingestion of ferrous sulfate on the absorption of oral methotrexate in patients with rheumatoid arthritis.

2003· article· en· W2426687844 on OpenAlexaff
Sean Hamilton, Norman R.C. Campbell, Mohamedtaki Kara, Jocelyn Watson, Margaret Connors

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFerrousIngestionRheumatoid arthritisPlaceboMethotrexateMedicineCrossover studySulfateExcretionInternal medicineArthritisOral administrationUrineGastroenterologyPharmacologyChemistryPathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate if ingestion of ferrous sulfate, 300 mg twice daily, will reduce the urinary excretion of unmetabolized methotrexate (MTX) in patients with rheumatoid arthritis (RA) who ingest 2 drugs concurrently, and determine if ferrous sulfate interferes with the absorption of oral MTX. METHODS: In this randomized double-blind placebo controlled crossover study, we compared the urinary excretion of unmetabolized MTX in 10 patients with RA who ingested 7.5 mg MTX as their weekly dose and took either ferrous sulfate 300 mg twice daily or placebo. RESULTS: Ten patients with RA taking 7.5 mg MTX orally once weekly had an average 24 h urine excretion of MTX (while taking 300 mg ferrous sulfate twice daily for one week) of 8.44 micromoles compared to 7.65 micromoles for patients taking placebo. The difference was not statistically significant (p = 0.50). CONCLUSION: Our results showed no less absorption of MTX for the placebo group compared to the group that took ferrous sulfate. These results do not support the hypothesis that ferrous sulfate interferes with the absorption of oral MTX.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.228
Teacher spread0.217 · 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

Citations3
Published2003
Admission routes1
Has abstractyes

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Same venuePubMed→Same topicRheumatoid Arthritis Research and Therapies→French-language works237,207→