Changing Transfusion Practice in Obstetrics and Gynecology: The Effect of Hospital-Wide Education [08M]
Bibliographic record
Abstract
INTRODUCTION: Red blood cell (RBC) transfusions are a potentially life-saving intervention in Obstetrics and Gynecology (O&G). With limited guidelines outlining appropriate use of RBC transfusions, clinicians often transfuse based solely on low hemoglobin values and habit. Our aim was to assess transfusion practices at a Canadian tertiary care center before and after a hospital-wide blood management educational campaign based on the Choosing Wisely toolkit. METHODS: Following approval from our Institutional Review Board, we conducted a retrospective chart review of all patients who received a RBC transfusion while admitted under an O&G provider in two 12-month periods, before and after the intervention. The campaign consisted of Grand Rounds presentations, formal and informal teaching, and posters placed around the hospital. Appropriateness was determined from a set of criteria composed of the presence or absence of active bleeding, initial hemoglobin, and number of units ordered at a time. RESULTS: Before and after transfusion rates were 1.8% and 1.2% respectively (83/4,610 vs 55/4,618 P=.016). There was a 52% reduction in total number of RBC units transfused (229 vs 111 P<.001), a 33% reduction in number of patients transfused (83 vs 55 P=.016), and fewer multiple unit transfusions without reassessment (39 vs 13 P=.005). The rate of transfusion appropriateness was low in both the pre and post intervention periods (46.5% vs 50.7% P=.59). CONCLUSION: Following a hospital-wide education campaign, there was a marked decrease in overall use of transfusion reflecting adoption of a more restrictive transfusion practice. The low rate of transfusion appropriateness represents an opportunity for further improvement.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".