Reduced birthweight in short or primiparous mothers: physiological or pathological?
Bibliographic record
Abstract
OBJECTIVE: Customisation of birthweight-for-gestational-age standards for maternal characteristics assumes that variation in birth weight as a result of those characteristics is physiological, rather than pathological. Maternal height and parity are among the characteristics widely assumed to be physiological. Our objective was to test that assumption by using an association with perinatal mortality as evidence of a pathological effect. DESIGN: Population-based cohort study. SETTING: Sweden. POPULATION: A total of 952 630 singletons born at > or =28 weeks of gestation in the period 1992-2001. METHODS: We compared perinatal mortality among mothers of short stature (<160 cm) versus those of normal height (> or =160 cm), and primiparous versus multiparous mothers, using an internal reference of estimated fetal weight for gestational age. The total effects of maternal height and parity were estimated, as well as the effects of height and parity independent of birthweight (controlled direct effects). All analyses were based on fetuses at risk, using marginal structural Cox models for the estimation of total and controlled direct effects. MAIN OUTCOME MEASURES: Perinatal mortality, stillbirth, and early neonatal mortality. RESULTS: The estimated total effect (HR; 95% CI) of short stature on perinatal death among short mothers was 1.2 (95% CI 1.1-1.3) compared with women of normal height; the effect of short stature independent of birthweight (controlled direct effect) was 0.8 (95% CI 0.6-1.0) among small-for-gestational-age (SGA) births, but 1.1 (95% CI 1.0-1.3) among non-SGA births. Similar results were observed for primiparous mothers. CONCLUSIONS: The effect of maternal short stature or primiparity on perinatal mortality is partly mediated through SGA birth. Thus, birthweight differences resulting from these maternal characteristics appear not only to be physiological, but also to have an important pathological component.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".