Determinants of Small for Gestational Age Birth at Term
Bibliographic record
Abstract
BACKGROUND: Being born small for gestational age (SGA) is an indicator of intrauterine growth restriction (IUGR) and later health risks. This study investigated determinants of severe and moderate SGA (respectively, birthweight <3rd percentile and 3rd to <10th percentile for gestational age and sex). METHODS: A total of 2195 term pregnancies from a prospective cohort were studied. Prenatal data arose from maternal interview at 10-22 weeks of gestation and perinatal data were collected from hospital charts. Severe and moderate SGA were classified by Canadian population standards. Risk factors for SGA were identified from fitting multivariable logistic regression models. RESULTS: Multivariable associations with severe SGA were: maternal age ≥ 35 [odds ratio (OR) 3.2 [95% confidence interval (CI) 1.4, 6.9]], maternal smoking during pregnancy (OR 5.3 [95% CI 2.4, 11.7]), preeclampsia (OR 4.6 [95% CI 1.6, 13.2]) and threatened preterm labour (OR 3.9 [95% CI 1.3, 11.4]). Primiparity was associated with both severe and moderate SGA with OR 2.4 [95% CI 1.1, 5.1] and OR 1.9 [95% CI 1.3, 2.9] respectively. Underweight pre-pregnancy body mass index was associated with moderate SGA (OR 2.4 [95% CI 1.2, 5.0]). Inclusion of placental weight, in the final model attenuated the associations. CONCLUSIONS: This study demonstrated different determinants for severe and moderate SGA. We speculate that the majority of severe SGA infants are IUGR while moderate SGA infants may be a mixture of IUGR and constitutionally small newborns. This study has also contributed evidence linking preterm labour and SGA as two, potentially related, outcomes of overlapping causal mechanisms reflective of ischaemic placental disease.
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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 | 0.004 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".