Vacuum-induced tamponade for managing postpartum hemorrhage: a systematic review
Bibliographic record
Abstract
OBJECTIVE: Postpartum hemorrhage is a leading cause of maternal mortality and morbidity around the globe. The novel low-suction vacuum hemorrhage device (VHD) provides an alternative treatment option for cases of postpartum hemorrhage when first-line uterotonic agents fail. This systematic review aims to review current data evaluating the overall efficacy and safety of VHDs in treating postpartum hemorrhage. METHODS: We searched CINAHL Ultimate, Academic Search Premier, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, MEDLINE with Full Text, and PubMed and reference lists of retrieved studies for eligible studies that included outcomes of effectiveness, efficacy, or safety. Two independent reviewers used Covidence.org to screen Titles and Abstracts for 69 studies of which six were included in the analysis. Secondary outcomes measured across studies included time to bleeding control, total device deployment time, and adverse effects. RESULTS: = 1018 participants) included studies conducted in Indonesia, the United States, Switzerland, and Canada. The VHDs were found to have 90% effectiveness in achieving bleeding control across the studies. For most patients, this was achieved in <5 min and required a total device deployment time of 3 h. Reported adverse events were not considered life-threatening, including endometritis in 11 patients and red blood cell transfusions in 38% of patients. CONCLUSION: VHDs have the potential to be used as a rapidly effective means for mechanical intervention of postpartum hemorrhage. The efficacy and safety of VHDs must be further studied at the randomized controlled trial level to determine their clinical usage.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".