Utilization of frozen plasma in <scp>O</scp>ntario: a provincewide audit reveals a high rate of inappropriate transfusions
Bibliographic record
Abstract
BACKGROUND: Frozen plasma (FP) is frequently transfused inappropriately, an intervention that results in risk without benefit for the patient. To better understand current utilization practices in our region, we undertook a provincewide prospective audit to evaluate the clinical indications and appropriateness of FP transfusion. STUDY DESIGN AND METHODS: All hospitals in the Canadian province of Ontario with transfusion medicine services were invited to participate in a 5-day audit of FP utilization. FP dose, indication, and clinical patient data were collected for each transfusion request. Indications for FP transfusions were independently adjudicated as appropriate, inappropriate, or indeterminate based on predefined criteria. RESULTS: Seventy-six (49%) of 155 invited hospitals participated in the audit, which included 573 requests for 2012 units of FP. A total of 559 transfusions (1909 units) were administered. Of 573 requests, 164 (28.6%) were deemed inappropriate most often because: 1) they were administered to patients with an international normalized ratio below 1.5 or 2) they were administered in absence of bleeding or emergency surgery. The most frequent indications for FP transfusions were before surgery and warfarin reversal. Overall, patients admitted to the clinical areas of surgery, internal medicine, and the emergency department represented the largest users of FP, but this varied by hospital type (community vs. academic). The most frequently requested doses of FP were 2 and 4 units. CONCLUSION: This point-prevalence hospital audit revealed that transfusion of FP is frequently inappropriate. Focusing on reducing the two most common reasons for inappropriate FP transfusions could lead to a significant improvement in FP utilization.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".