Platelet concentrate functionality assessed by thromboelastography or rotational thromboelastometry
Bibliographic record
Abstract
BACKGROUND: There is poor correlation between in vivo platelet concentrate (PC) transfusion outcome and in vitro tests, which typically do not test the functional effectiveness of platelets (PLTs), but rather measure PLT characteristics. We hypothesize that the application of thromboelastography (TEG) or rotational thromboelastometry (ROTEM) to evaluate the procoagulant activity of stored PLTs can predict PLT quality and, ultimately, distinguish among hyper- and nonresponsive PCs. Additionally, we hypothesize that due to their procoagulant properties, PLT microvesicles (PMVs) contribute to the clot signature in these methods. STUDY DESIGN AND METHODS: After the TEG assays were validated, buffy coat PCs were evaluated during the storage time and reconstituted with frozen plasma to different PLT concentrations. Poor quality PCs were generated and assessed by TEG and other in vitro tests. The contribution of PMVs to the TEG clot signature was assessed. RESULTS: Hemostatic analysis showed no significant change in maximum amplitude (MA) during storage of PCs up to Day 10. On Day 8 of storage, PCs that had been manipulated to have poor quality showed a significant decrease in MA. PMV-rich samples contributed to a significant increase in MA, and PMV count showed a significant correlation with maximum clot formation (r = 0.51, p < 0.01). CONCLUSION: TEG was optimized for use with buffy coat PCs, although it was found to lack sensitivity to detect normal storage-related quality changes. Hemostatic measurement was sufficiently sensitive to dissect PLT and PMV contributions to clot formation and to detect PCs stored under poor conditions.
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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 | 0.001 |
| 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) | 0.003 | 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".