Bibliographic record
Abstract
Background: Postpartum hemorrhage (PPH) remains a common cause of maternal mortality worldwide, mainly caused by uterine atony. Medical intervention plays an important part in prevention and therapies of PPH. Prophylactic interventions include the use of uterotonic drugs. We elaborated the consistency of national and international guidelines on those medical approaches. Materials and methods: Medical approaches in PPH were extracted from recent publications. Furthermore, the current guidelines of the World Health Organization, the FIGO and of the American, British,and Canadian of Obstetricians and Gynecologists on PPH were analyzed. Results: Use of oxytocin after delivery of the anterior shoulder is the most important and effective component of this practice. However, the examined guidelines fail to give unequivocal recommendations on further uterotonics in PPH, which may partially be attributed to differing publication dates of the guidelines. Conclusion: Appropriate management of postpartum hemorrhage requires prompt diagnosis and treatment . International guidelines on PPH are characterized by differing recommendations. However, recent publications suggest that adhering to local guidelines significantly reduces the prevalence of severe PPH.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".