Bleeding disorders and postpartum hemorrhage by mode of delivery: a retrospective cohort study
Bibliographic record
Abstract
Background: Pregnant persons with bleeding disorders and their potentially affected newborns are at a higher risk of peripartum bleeding complications. The safest mode of delivery for persons with bleeding disorders remains debated, leading to uncertainties in decision-making between the patient and her multidisciplinary team. Objectives: This study aimed to describe maternal outcomes for pregnant persons with bleeding disorders by mode of delivery and to examine whether postpartum hemorrhage (PPH) and neonatal hemorrhagic manifestations are associated with the mode of delivery. Methods: We collected retrospective data on pregnant persons with bleeding disorders who delivered at a single center from 2010 to 2021. Descriptive statistics, Fisher exact test, and odds ratios were used for analysis. Results: A total of 82 pregnancies in 56 subjects were included. Hemophilia A and von Willebrand disease represented the largest cohort, at 30% (17/56) each. Overall rates of primary and secondary PPH were 7.3% (6/82) and 17.4% (12/69), respectively. We did not find a statistically significant difference between mode of delivery and PPH. Upon comparing vaginal and cesarian deliveries, we found an odds ratio of 0.7 (95% CI, 0.1-3.4) for primary PPH and 2.6 (95% CI, 0.4-16.4) for secondary PPH. One male newborn with severe hemophilia A was treated for a suspected intracranial hemorrhage. Conclusion: In our cohort, high rates of PPH remained an important complication for pregnant persons with bleeding disorders. There was no significant difference in PPH based on modes of delivery. The small sample size likely limited the power of our study, and consequently, future larger studies are needed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".