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Effect of Passive Smoking on Theophylline Clearance in Children

2001· article· en· W1971289153 on OpenAlexaff
Patrick Mayo

Bibliographic record

VenueTherapeutic Drug Monitoring · 2001
Typearticle
Languageen
FieldMedicine
TopicRespiratory and Cough-Related Research
Canadian institutionsAlberta HealthUniversity of Alberta HospitalAlberta Hospital Edmonton
Fundersnot available
KeywordsMedicineTheophyllineTobacco smokePassive smokingAminophyllineAsthmaExacerbationPopulationAnesthesiaSmokeInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

The author investigated the effects of passive tobacco smoking on the metabolism of theophylline in a pediatric population. In a retrospective analysis of 201 children admitted to a pediatric unit for asthma, 31 were identified with an acute exacerbation of asthma of noninfectious origin in which environmental exposure to tobacco smoke could be established. The parents were known smokers with a minimum 1-pack-per-day habit. An age-and gender-matched control population of children was then identified who had an acute exacerbation of asthma without any environmental exposure to tobacco smoke. In addition, the patients in both groups received the same dose of intravenous aminophylline for a minimum of 48 hours to ensure steady-state conditions. Total body clearance of theophylline was significantly elevated in the children exposed to environmental tobacco smoke (1.36 +/- 0.09 vs. 0.90 +/- 0.04 mL/min per kg, p < 0.0001). Steady-state serum levels were significantly lower in the passive smoking group (55.3 +/- 2.8 vs. 73.2 +/- 3.3 p < 0.00001) for those receiving nearly identical intravenous doses. The length of hospital stay was longer in the group exposed to passive smoke (4.4 +/- 2.6 vs. 2.9 +/- 1.3 days, p < 0.05). The clearance of theophylline is greater in asthmatic children exposed to passive tobacco smoke than in asthmatic children not exposed to passive tobacco smoke. These findings suggest that passive smoking may increase the clearance of other drugs metabolized in a manner similar to theophylline.

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)0.001
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 score0.275
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.015
GPT teacher head0.324
Teacher spread0.309 · 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

Citations27
Published2001
Admission routes1
Has abstractyes

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