Comparison of Maternal Risk Factors between Placental Abruption and Placenta Previa
Bibliographic record
Abstract
The purpose of this study was to compare risk factors between placental abruption and placenta previa among primiparous and multiparous singleton pregnancies. We analyzed data from a population-based retrospective cohort with singleton pregnancies in the United States for 1995 to 2000. Maternal risk factors for placenta previa and placental abruption were examined using multiple logistic regressions. A total of 5,630,854 primiparous and 11,026,768 multiparous singleton pregnancies were available for final analyses after excluding subjects with missing information on outcomes or important exposures. Placental abruption was recorded in 4.8 per 1000 primiparous singleton births and 5.9 per 1000 multiparous singleton pregnancies. The occurrence of placenta previa was 1.9 per 1000 primiparous singleton pregnancies and 3.9 per 1000 multiparous singleton pregnancies. The effects of maternal age, race, parity, and previous cesarean section were stronger on placenta previa than on placental abruption, and the effects of cigarette smoking, alcohol drinking, and prenatal care were stronger on placental abruption than on placenta previa. A composite outcome of selected medical and pregnancy complications was related with placental abruption but not with placental previa. Placental abruption is more likely to be affected by conditions occurring during pregnancy, and placenta previa is more likely to be affected by conditions existing prior to pregnancy.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".