Maternal Smoking and Fetal Erythropoietin Levels
Bibliographic record
Abstract
In Brief Objective To determine the influence of maternal smoking on fetal erythropoietin concentrations in health term pregnancies and test the correlation between cotinine, a biomarker of maternal smoking, and erythropoietin levels in fetuses. Methods We invited women with healthy term pregnancies to participate in the study, excluding those with conditions previously known to be associated with elevated fetal erythropoietin levels. We recorded demographic data, smoking status, and labor outcome prospectively for each patient. Umbilical venous samples were collected, and serum was stored at −70C to be analyzed later for erythropoietin and cotinine. Umbilical arterial samples were tested for pH and base excess determination. We compared fetal erythropoietin and cotinine between smokers and nonsmokers and examined correlations between erythropoietin and cotinine. Kruskal-Wallis test, t test, median test, and Spearman rank correlation test were used when appropriate. Statistical significance was P < .05. Results We recruited 35 nonsmokers and 26 smokers and analyzed their samples. The two groups were comparable in demographics and birth outcomes, except for birth weights, which were lower in smokers. Fetal erythropoietin concentrations increased significantly with increasing maternal cigarette consumption, ranging from none to more than 15 cigarettes per day (P = .03). There was positive correlation between fetal erythropoietin and cotinine concentrations (r = .41; P = .04), suggesting a dose-response relationship. Conclusion Fetuses of smokers had increased erythropoietin concentrations that correlate positively with fetal cotinine levels; which suggests an increased risk of subacute hypoxia related to degree of maternal cigarette consumption. Fetuses of smokers have increased blood erythropoietin concentrations, suggesting subacute hypoxia; fetal erythropoietin correlates positively with fetal cotinine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".