Thromboelastography and thrombin generation assessments for pediatric severe hemophilia A patients are highly variable and not predictive of clinical phenotypes
Bibliographic record
Abstract
Background: Severe hemophilia A (SHA) patients vary in severity of bleeding, arthropathy, and requirements for replacement factor VIII (FVIII). Baseline hemostatic activity assays using calibrated automated thrombography (CAT) and thromboelastography (TEG) may offer insights into the physiological basis of clinical heterogeneity. Objectives: Use CAT and TEG to measure baseline hemostatic activity in a cohort of 30 pediatric SHA patients with available clinical data. Determine effect of contact activation inhibition with corn trypsin inhibitor (CTI). Assess heterogeneity among patients for baseline hemostatic activity and examine correlations between assay results and clinical parameters including FVIII dosing regimen, von Willebrand factor level, and Pettersson arthropathy score. Methods: SHA blood after FVIII washout was subjected to TEG, and platelet-rich (PRP) and platelet-poor plasma was used for CAT assays. Varying concentrations of tissue factor (TF) were used. Statistical analysis examined relationships between assay results, and clinical parameters. Results: CTI treatment was required to obtain TEG and CAT results representative of baseline hemostatic activity. Weak activity was observed in assays with low TF concentrations (0.5-2 pM), and most but not all samples approached normal activity levels at high TF concentrations (10-20 pM). A significant positive correlation was observed between results of TEG and CAT-PRP assays. Correlations were not detected between hemostatic assay results and clinical parameters. Conclusions: hemostatic assay results of samples containing platelets showed concordance. Assay results were not predictive of FVIII requirements or correlated with other clinical parameters. SHA patient heterogeneity is influenced by factors other than baseline hemostatic activity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".