Audit of appropriate use of platelet transfusions: validation of adjudication criteria
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Platelet (PLT) transfusions must be used appropriately, as they are in chronic short supply, costly and risky to patients. The goals of this audit were to: (1) validate preset adjudication criteria through an audit of appropriateness at four large academic hospitals; (2) identify variability in appropriateness across medical services, physician specialties or hospital locations; and (3) inform logistical or educational interventions that may reduce inappropriate use. MATERIALS AND METHODS: A chart review of two hundred patients receiving PLT transfusions was performed. Fifty consecutive transfusion episodes per site were audited in detail. Each transfusion episode was independently adjudicated as appropriate or inappropriate by two transfusion specialists based on predetermined criteria. RESULTS: The adjudication criteria performed well with simple agreement of 95% (kappa statistic 0·83) between reviewers. Overall, 78% (95% CI: 72-84%) of PLT transfusions were adjudicated as appropriate, with results varying significantly by hospital site (range 62-94%). Prophylactic transfusions for non-bleeding patients had the highest proportion of appropriateness (85%, n = 80), and therapeutic transfusions for bleeding patients had the lowest (73%, n = 99). The lowest levels of appropriate platelet transfusions were observed in the operating rooms (60%) and when ordered by the general surgery service (55%). CONCLUSIONS: One in five platelet transfusions may be unnecessary, suggesting that interventions to improve PLT transfusion practice are warranted.
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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 | 0.147 | 0.331 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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 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".