Rapid Assessment of Platelet Function Using Thromboelastography and Small Volumes of Citrated Whole Blood.
Bibliographic record
Abstract
Abstract Platelet function disorders are a key cause of abnormal bleeding, and diagnosis is challenging because: platelet abnormalities are diverse, affecting many aspects of function; variability in platelet function testing in clinical laboratories makes it difficult to compare results; large blood volumes required for platelet function analysis make it difficult to perform in neonatal patients; manipulation of platelet rich plasma used for platelet aggregation can lead to test variability; platelet aggregation curves are difficult to interpret in thrombocytopenic patients. We describe a method of testing platelet function using citrated whole blood and thromboelastography (TEG) that overcomes some of these limitations. Commercially-available platelet mapping kits allow the effects of the platelet agonists adenosine diphosphate (ADP) and arachidonic acid (AA) to be assessed via a TEG assay where reptilase and activated factor XIII produce fibrin clots independent of thrombin in heparinized whole blood. The activation and aggregation of platelets is quantified by measuring the difference in maximum amplitude (MA) between unstimulated samples, which form weak fibrin-only clots, and samples with agonists added, which form stronger clots containing fibrin and activated/aggregated platelets. Platelet mapping was used as the basis for a TEG assay which can be used to assess platelet responses to a wide range of stimuli - including ADP, AA, epinephrine, collagen, U46619 (thromboxane-A2 receptor agonist), SFLLRN (PAR-1 thrombin receptor activating peptide) and AYPGKF (PAR-4 activating peptide) - in small samples (330μL) of citrated native (CN) blood or plasma to which heparin is added to a concentration of 20U/mL. Samples were recalcified by adding calcium chloride to 10mM (necessary for the function of reptilase and FXIIIa), and other reagent volumes were the same as in platelet mapping assays, with fibrin activator prepared at 1/2 regular strength. The concentrations of platelet agonists were: collagen 51μg/ml, epinephrine 0.27μM, ADP 5.4μM, arachidonic acid 135μg/mL, U46619 2.6μM, SFLLRN 6.76μM and AYPGKF 34μM. These concentrations produced TEG MA values in heparinated fibrin-activated CN blood from a panel of normal individuals comparable to those obtained from recalcified CN blood in the absence of heparin (the fibrin/platelet response control). The platelet response was rapid with maximum amplitudes reached within 10 minutes for all agonists except collagen, which required >30 minutes to produce maximum amplitude. We have found this TEG platelet-response assay to be useful in detecting platelet function abnormalities, producing results which correlate with and extend those of other platelet function tests. For example in one patient a weak response to epinephrine corresponded to similar platelet aggregation results, and in another the TEG assay detected a weak PAR-1 response not specifically detected in other tests. The assay has also proven useful in assessing platelet function in blood and plasma having low platelet concentrations (<50 x 10E9/L) from experimental or pathological causes (e.g. thrombocytopenia), in titrating platelet responses to agonists and in assessing the effects of antiplatelet agents in vivo and in vitro. Thus this TEG platelet function assay has the advantages of speed, ease of use, flexibility, adaptability to low platelet concentrations and sample economy, requiring small volumes of citrated blood which can be used for other coagulation assays and platelet response tests.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".