Heavily Smoking Women Who Cannot Quit in Pregnancy: Evidence of Pharmacokinetic Predisposition
Bibliographic record
Abstract
SUMMARY: Smoking in pregnancy is associated with a well-characterized increase in perinatal risks. Despite their wish to discontinue smoking, some pregnant women cannot stop. To characterize nicotine and cotinine levels in women who could not quit smoking after the first trimester, the authors recruited 19 white women (age 17-41 years) between 14-23 weeks of gestation who could not quit smoking. They started smoking at ages 11-22 years (mean 14.5) and smoked for 17 +/- 6 years. They had their first cigarettes 5-60 minutes after waking up (mean 12). Nicotine levels were compared with those expected in white patients in the general population, and the cotinine levels per cigarette smoked were compared with the population-based values. Sixteen of the 19 women had nicotine levels substantially lower than those expected. The mean level of serum cotinine produced by one cigarette per day was 19.1 +/- 15.8 ng/mL (range 6.1-67). The expected levels in white patients in the general population are 13 +/- 7.7 ng/mL. The data suggest that pregnant women who cannot quit heavy smoking in the second trimester form a selective group with pharmacokinetic predisposition to a high rate of nicotine metabolism.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".