Plasma transfusion practices: A multicentre electronic audit
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Plasma is often transfused to patients with bleeding or requiring invasive procedures and with abnormal tests of coagulation. Chart audits find half of plasma transfusions unnecessary, resulting in avoidable complications and costs. This multicentre electronic audit was conducted to determine the proportion of plasma transfused without an indication and/or at a sub-therapeutic dose. METHODS: Data were extracted on adult inpatients in 2017 at five academic sites from the hospital electronic chart, laboratory information systems and the Canadian Institute for Health Information Discharge Abstract Database. Electronic criteria for plasma transfusion outside recommended indications were: (1) international normalized ratio (INR) < 1.5 with no to moderate bleeding; (2) INR ≥ 1.5, with no to mild bleeding and no planned procedures; and (3) no INR before or after plasma infusion. Sub-therapeutic dose was defined as ≤2 units transfused. RESULTS: In 1 year, 2590 patients received 6088 plasma transfusions encompassing 11,490 units of plasma occurred at the five sites. 77.7% of events were either outside indications or under-dosed. Of these, 34.8% of plasma orders had no indication identified, and 62% of these occurred in non-bleeding patients and no planned procedure with an isolated elevated INR. 70.7% of transfusions were under-dosed. Most plasma transfusions occurred in the intensive care unit or the operating room. Inter-hospital variability in peri-transfusion testing and dosing was observed. CONCLUSION: The majority of plasma transfusions are sub-optimal. Local hospital culture may be an important driver. Electronic audits, with definitions employed in this study, may be a practical alternative to costly chart audits.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".