Efficacy of Intra-Uterine Tamponade Balloon in Post-Partum Hemorrhage after Cesarean Delivery: An Impact Study
Bibliographic record
Abstract
Invasive therapies (surgery or radiological embolization) are used to control severe post-partum hemorrhage. The intra-uterine tamponade balloon is a potential alternative, well documented after vaginal delivery. However, available data on its use after cesarean delivery remain scarce. This study assessed the efficacy of the intra-uterine tamponade balloon during post-partum hemorrhage in a cesarean delivery setting. Using a retrospective impact design, post-partum hemorrhage-related outcomes before (“pre-balloon” period) versus after implementation of intra-uterine tamponade balloon (“post-balloon” period) were compared. All women with post-partum hemorrhage requiring potent uterotonic treatment with prostaglandins after cesarean delivery over a 9-year period were eligible. The primary outcome was the rate of invasive procedure (conservative surgery, radiological embolization and/or hysterectomy). p < 0.05 was considered statistically significant. A total of 279 patients were included (140 vs. 139). Most baseline characteristics were comparable between the two studied periods. The success rate of the intra-uterine tamponade balloon was 82%, and no related complications occurred. Rates of invasive procedures and transfusion were significantly reduced (28.6% vs. 11.5%, p < 0.001 and 44.3% vs. 28.1%, p = 0.006 respectively) during the “post-balloon” period, and length of hospital stay was shorter (p < 0.001). Implementation of intra-uterine tamponade balloon during post-partum hemorrhage after cesarean delivery appears to be safe and effective, with a decrease in both invasive procedures and transfusion rates.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".