Anesthetic and Transfusion Management in Placenta Accreta Spectrum: Lessons From a Resource-Limited Setting and Mini-Review
Bibliographic record
Abstract
Placenta accreta spectrum (PAS) is a severe obstetric condition characterized by abnormal placental invasion of the myometrium, often resulting in massive hemorrhage and high maternal morbidity and mortality. Optimal management requires early recognition, multidisciplinary coordination, and prompt activation of massive transfusion protocols (MTPs). We report the case of a 41-year-old gravida 3 woman at 36 - 37 weeks of gestation, with two prior cesarean deliveries and a transverse fetal lie, who developed life-threatening hemorrhage during cesarean section for PAS. Spinal anesthesia was promptly converted to general anesthesia to allow safe surgical intervention, which included hysterectomy, hemostatic and vaginal sutures, bladder repair, and massive transfusion. Postoperatively, the patient was stabilized in the intensive care unit and discharged in good condition after 10 days. This case demonstrates that early MTP activation, rapid anesthetic adaptation, and coordinated multidisciplinary care can result in favorable outcomes even in resource-limited settings. It underscores the importance of preparedness, flexible intraoperative decision-making, and collaboration across obstetric, anesthetic, surgical, and critical care teams in the management of high-risk PAS cases.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".