Towards a universal definition of postpartum hemorrhage: retrospective analysis of Chinese women after vaginal delivery or cesarean section
Bibliographic record
Abstract
Postpartum hemorrhage (PPH) is a leading cause of maternal morbidity and mortality, yet it is inconsistently defined, preventing accurate estimation of its incidence and identification of risk factors. Here we began to explore a unified definition of PPH that may be valid for vaginal delivery and cesarean section.Medical records of women who underwent vaginal delivery or cesarean section at our tertiary medical center between January and December 2018 were retrospectively analyzed. Patients who delivered by each route were compared in terms of PPH incidence and risk factors depending on different blood loss cut-off values.A total of 560 vaginal deliveries and 393 cesarean sections were analyzed. Vaginal deliveries were associated with significantly greater blood loss based on change of hemoglobin level, but significantly lower blood loss based on clinical estimation. When PPH was defined as blood loss ≥500 ml based on change of hemoglobin level, its incidence was 57.7% for vaginal deliveries and 28.2% for cesarean sections. The corresponding incidences were 15.4% and 3.3% when PPH was defined as blood loss ≥1000 ml based on change of hemoglobin levels. Independent risk factors for PPH in vaginal deliveries were lateral perineotomy (OR 2.835, 95%CI 1.694-4.743), suturing by a junior physician (OR 3.456, 95%CI 2.005-5.956), and long time from delivery of placenta to return to the recovery room (OR 1.013, 95%CI 1.003-1.022). A risk factor for PPH in cesarean sections was a long time from delivery of the fetus until the end of the operation.PPH is a significantly underestimated obstetric problem, especially in vaginal deliveries. Regardless of delivery route, hemoglobin-based blood loss of 500 ml and 1000 ml may be useful, respectively, as early warning and diagnostic cut-off values.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".