Provider experiences with improvised uterine balloon tamponade for the management of uncontrolled postpartum hemorrhage in Kenya
Bibliographic record
Abstract
OBJECTIVE: To understand healthcare providers' experiences with improvised uterine balloon tamponade (UBT) for the management of uncontrolled postpartum hemorrhage (PPH). METHODS: In a qualitative descriptive study, in-depth semi-structured interviews were conducted between November 2014 and June 2015 among Kenyan healthcare providers who had previous experience with improvising a UBT device. Interviews were conducted, audio-recorded, and transcribed. RESULTS: Overall, 29 healthcare providers (14 nurse-midwifes, 7 medical officers, 7 obstetricians, and 1 clinical officer) were interviewed. Providers perceived improvised UBT as valuable for managing uncontrolled PPH. Reported benefits included effectiveness in arresting hemorrhage and averting hysterectomy, and ease of use by providers of all levels of training. Providers used various materials to construct an improvised UBT. Challenges to improvising UBT-e.g. searching for materials during an emergency, procuring male condoms, and inserting fluid via a small syringe-were reported to lead to delays in care. Providers described their introduction to improvised UBT through both formal and informal sources. There was universal enthusiasm for widespread standardized training. CONCLUSION: Improvised UBT seems to be a valuable second-line treatment for uncontrolled PPH that can be used by providers of all levels. UBT might be optimized by integrating a standard package across the health system.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".