Evaluating the appropriateness of platelet transfusions compared with evidence‐based platelet guidelines: An audit of platelet transfusions at 57 hospitals
Bibliographic record
Abstract
Abstract Background Platelet transfusions are used to prevent or control bleeding in patients with thrombocytopenia or platelet dysfunction. The pretransfusion platelet count threshold has been studied extensively in multiple patient settings yielding high‐quality evidence that has been summarized in several comprehensive evidence‐based platelet guidelines. Study Design and Methods A prospective 12‐week audit of consecutive platelet transfusions using validated and evidence‐based adjudication criteria was conducted. Patient demographic, laboratory, and transfusion details were collected with an electronic audit tool. Each order was adjudicated either electronically or independently by two transfusion medicine physicians. The aim was to determine platelet transfusion appropriateness and common scenarios with deviations from guidelines. Results Fifty‐seven (38%) of 150 hospitals provided data on 1903 platelet orders, representing 90% of platelet usage in the region during the time period. Overall, 702 of 1693 adult (41.5%) and 133 of 210 pediatric orders (63.3%) were deemed inappropriate. The most common inappropriate platelet order was for prophylaxis in the absence of bleeding or planned procedure in patients with hypoproliferative thrombocytopenia and a platelet count over 10 x 10 9 /L (53% of inappropriate orders in adults and 45% in pediatrics). Platelet transfusions ordered with either a preprinted transfusion order set (odds ratio [OR], 1.97; 95% confidence interval [CI], 1.44‐2.73) or technologist prospective screening (OR, 1.40; 95% CI, 1.10‐1.78) were more likely to be appropriate. Conclusion There is a discrepancy between clinical practice and evidence‐based platelet guidelines. Broad educational and system changes will be needed to align platelet transfusion practice with guideline recommendations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".