Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".