Impact of Preeclampsia and Gestational Hypertension on Birth Weight by Gestational Age
Bibliographic record
Abstract
The predominant etiologic theory of preeclampsia is that reduced uteroplacental perfusion is the unique pathogenic process in the development of preeclampsia. Decreased uteroplacental blood flow would result in lower birth weights. To date, no study has assessed the effect of preeclampsia on birth weight by gestational age. Thus, the authors conducted a retrospective cohort study based on 97,270 pregnancies that resulted in delivery between 1991 and 1996 at 35 hospitals in northern and central Alberta, Canada. Differences in mean birth weight between women with preeclampsia and normotensive women ranged from -547.5 g to 239.5 g for gestational age categories ranging from < or = 32 weeks to > or = 2 weeks. The birth weights were statistically significantly lower among mothers with preeclampsia who delivered at < or = 37 weeks, with an average difference of -352.5 g. However, the birth weights were not lower among preeclamptic mothers who delivered after 37 weeks (average difference of 49.0 g). In Alberta, 61.2% of preeclamptic patients gave birth after 37 weeks of gestation. The authors conclude that babies born to mothers with preeclampsia at term have fetal growth similar to that of babies born to normotensive mothers. This finding does not endorse the currently held theory that reduced uteroplacental perfusion is the unique pathophysiologic process in preeclampsia.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".