The Influence of Cigarette Smoking on Antenatal Growth, Birth Size, and the Insulin-Like Growth Factor Axis
Bibliographic record
Abstract
BACKGROUND: Maternal smoking during pregnancy is associated with a reduction in birth size. Very few studies have collated changes in fetal biometry, neonatal anthropometry, biochemical factors involved in fetal growth, and measures of uterine and umbilical blood flow. METHODS: We related smoking status in 1650 low-risk, singleton Caucasian pregnancies delivering at term to measures of fetal growth, uterine and umbilical artery blood flow, placental appearance, birth size, and cord concentrations of IGF-I and -II and IGF binding protein (IGFBP)-3. RESULTS: Mothers who smoked in pregnancy were younger (P < 0.001) and shorter (P = 0.03) and from lower socioeconomic groups (P < 0.001). Mean umbilical artery blood flow at 20 wk gestation was not associated with smoking status but was significantly higher in smokers at 30 wk (P = 0.006). Uterine artery blood flow was unaffected. Smoking was associated with an increase in the percentage of abnormal placentas in a dose-dependent manner and with a 3.1-fold increased risk (odds ratio 3.1, 95% confidence interval 1.3-7.6) of abnormal umbilical artery blood flow (P = 0.009). Smoking was associated with a reduction in fetal femur length (P = 0.005) and abdominal circumference as well as birth weight, length, and head circumference but not skinfold thickness. Cord plasma concentrations of IGF-I and IGFBP-3 were lower in the babies of mothers who had smoked (P = 0.02 and P = 0.01, respectively). CONCLUSION: We concluded that maternal smoking is associated with an altered placental appearance on ultrasonography, increased umbilical artery blood flow resistance, and a reduction in longitudinal and intraabdominal organ growth. Circulating concentrations of IGF-I and IGFBP-3 along with measures of birth size but not markers of body fat are reduced, suggesting smoking results in a reduction in organ size and function.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".