The Risk of Stillbirth at Term and Timing of Delivery in Obese Women [38D]
Bibliographic record
Abstract
INTRODUCTION: Studies have shown that a high body mass index (BMI), expressed in kg/m2, is an independent risk factor for stillbirth. The purpose of this study was to determine an optimal time of delivery in obese women in order to decrease the risk of stillbirth in this population. METHODS: We conducted a retrospective population-based cohort study using the CDC's Period Linked Birth-Infant Death and Fetal Death data. The study population included all singleton, term births with a recorded pre-pregnancy BMI that occurred between 2014 and 2017, inclusively. The risk of stillbirths in each BMI class was estimated at each gestational week from 37 weeks and onwards. RESULTS: Of the 12,742,980 births in our cohort that met study criteria, 46.8% were to women with a normal BMI, 26.9% were to women who were classified as overweight, 14.5% were to women in obesity class I, 7.3% in obesity class II, and 4.8% in obesity class III. As compared to women at 41 weeks with a normal BMI, there was a higher risk of stillbirth in women of obesity class I at 39 weeks (OR 1.15 95% CI 1.00–1.31), at 38 weeks for obesity class II (OR 1.21 95% CI 1.04–1.41) and at 37 weeks for obesity class III (OR 1.30 95% CI 1.11–1.52). CONCLUSION: As compared to women with a normal BMI, there was a higher risk of stillbirth at term in women with each increase in BMI class. Consideration should be given to early induction among these women to reduce the risk of stillbirth.
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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 | 0.002 |
| 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 | 0.000 |
| 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".