Thrombin generation and bleeding in haemophilia A
Bibliographic record
Abstract
Haemophilia A displays phenotypic heterogeneity with respect to clinical severity. The aim of this study was to determine if tissue factor (TF)-initiated thrombin generation profiles in whole blood in the presence of corn trypsin inhibitor (CTI) are predictive of bleeding risk in haemophilia A. We studied factor(F) VIII deficient individuals (11 mild, 4 moderate and 12 severe) with a well-characterized 5-year bleeding history that included haemarthrosis, soft tissue haematoma and annual FVIII concentrate usage. This clinical information was used to generate a bleeding score. The bleeding scores (range 0-32) were separated into three groups (bleeding score groupings: 0, 0 and < or = 9.6, >9.6), with the higher bleeding tendency having a higher score. Whole blood collected by phlebotomy and contact pathway suppressed by 100 microg mL(-1) CTI was stimulated to react by the addition of 5 pM TF. Reactions were quenched at 20 min by inhibitors. Thrombin generation, determined by enzyme-linked immunosorbent assay for thrombin-antithrombin was evaluated in terms of clot time (CT), maximum level (MaxL) and maximum rate (MaxR) and compared to the bleeding score. Data are shown as the mean+/-SD. MaxL was significantly different (P < 0.001) between the groups: 504 +/- 114, 315 +/- 117 and 194 +/- 91 nM; with higher thrombin concentrations in the groups with lower bleeding scores. MaxR was higher in the groups with a lower bleeding score; 97 +/- 51, 86 +/- 60 and 39 +/- 16 nM min(-1) (P = 0.09). No significant difference was detected in CT among the groups, 5.6 +/- 1.3, 4.7 +/- 0.7 and 5.6 +/- 1.3 min. Our empirical study in CTI-inhibited whole blood shows that the MaxL of thrombin generation appears to correlate with the bleeding phenotype of haemophilia A.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".