A qualitative assessment of the impact of a uterine balloon tamponade package on decisions regarding the role of emergency hysterectomy in women with uncontrolled postpartum haemorrhage in Kenya and Senegal
Bibliographic record
Abstract
OBJECTIVES: To assess the impact of a every second matters for mothers and babies uterine balloon tamponade package (ESM-UBT) on provider decisions regarding emergency hysterectomy in cases of uncontrolled postpartum haemorrhage (PPH). DESIGN: Qualitative assessment and analysis of a subgroup extracted from a larger database that contains all UBT device uses among ESM-UBT trained health providers. SETTING: Health facilities in Kenya and Senegal with ESM-UBT training and capable of performing emergency hysterectomies. PARTICIPANTS: All medical doctors who had placed a UBT for uncontrolled PPH subsequent to implementation of ESM-UBT at their facility, and who also had the capabilities of performing emergency hysterectomies. PRIMARY OUTCOME MEASURES: The impact of ESM-UBT on decisions regarding emergency hysterectomy in cases of uncontrolled PPH. RESULTS: 30 of the 31 medical doctors (97%) who fulfilled the inclusion criteria were independently interviewed. Collectively the interviewed medical doctors had placed over 80 UBT devices for uncontrolled PPH since ESM-UBT implementation. All 30 responded that UBT devices immediately controlled haemorrhage and prevented women from being taken to emergency hysterectomy. All 30 would continue to use UBT devices in future cases of uncontrolled PPH. CONCLUSIONS: These preliminary data suggest that following ESM-UBT implementation, emergency hysterectomy for uncontrolled PPH may be averted by use of uterine balloon tamponade.
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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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".