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Record W2091523885 · doi:10.1089/thy.2013.0014

Ciprofloxacin and Rifampin Have Opposite Effects on Levothyroxine Absorption

2013· article· en· W2091523885 on OpenAlexafffund
Alyse S. Goldberg, Rommel G. Tirona, Linda Asher, Richard B. Kim, Stan Van Uum

Bibliographic record

VenueThyroid · 2013
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsWestern University
FundersLawson Health Research Institute
KeywordsCiprofloxacinLevothyroxineCrossover studyMedicineDosingPharmacokineticsAntibioticsPharmacologyAbsorption (acoustics)Internal medicineAntibacterial agentPlaceboDrug interactionGastroenterologyHormoneChemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Levothyroxine (L-T4) absorption varies between individuals, and can be affected by various concomitantly administered drugs. Case reports have indicated an association between cotreatment with ciprofloxacin or rifampin and hypothyroidism in patients on a stable L-T4 dose. METHODS: The effects of two antibiotics on T4 absorption were prospectively assessed in a double-blind, randomized, crossover fashion. Eight healthy volunteers received 1000 μg L-T4 combined with placebo, ciprofloxacin 750 mg, or rifampin 600 mg as single doses. We measured total plasma thyroxine (T4) concentrations over a 6-hour period after dosing using liquid chromatography-tandem mass spectrometry. For each study arm, areas under the T4 plasma concentration-time curve (T4 AUCs) were compared. RESULTS: Coadministration of ciprofloxacin significantly decreased the T4 AUC by 39% (p = 0.035), while, surprisingly, rifampin significantly increased T4 AUC by 25% (p = 0.003). CONCLUSION: Intestinal absorption of L-T4 is differentially affected by acute coadministration of ciprofloxacin or rifampin. Mechanistic studies focused on intestinal and possibly hepatic thyroid hormone transporters are required to explain the observed drug interactions with L-T4.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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

Citations25
Published2013
Admission routes2
Has abstractyes

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