Challenging the 30‐min rule for thawed plasma
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Frozen plasma (FP) is thawed prior to transfusion and stored for ≤5 days at 1-6°C. The effect of temperature excursions on the quality and safety of thawed plasma during 5-day storage was determined. MATERIALS AND METHODS: Four plasma units were pooled, split and stored at ≤-18°C for ≤90 days. Test units T30 and T60 were exposed to 20-24°C (room temperature [RT]) for 30 or 60 min, respectively, on days 0 and 2 of storage. Negative and positive control units remained refrigerated or at RT for 5 days, respectively. On Day 5, test units were exposed once to RT for 5 h. Quality assays included stability of coagulation factors FV, FVII, FVIII, fibrinogen and prothrombin time. Bacterial growth was performed in units inoculated with ~1 CFU/ml or ~100 CFU/ml of Serratia liquefaciens, Pseudomonas putida, Pseudomonas aeruginosa or Staphylococcus epidermidis on Day 0. RESULTS: Testing results of all quality parameters were comparable between T30 and T60 units (p < 0.05). Serratia liquefaciens proliferated in cold-stored plasma, while P. putida showed variable viability. Serratia epidermidis and P. aeruginosa survived but did not grow in cold-stored plasma. Positive and negative controls showed expected results. Overall, no statistical differences in bacterial concentration between T30 and T60 units were observed (p < 0.05). CONCLUSION: Multiple RT exposures for 30 or 60 min do not affect the stability of coagulation factors or promote bacterial growth in thawed plasma stored for 5 days. It is therefore safe to expose thawed plasma to uncontrolled temperatures for limited periods of 60 min.
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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) | 0.001 | 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".