Clinical use of recombinant human activated factor VII (rFVIIa) in the prevention and treatment of bleeding episodes in patients with Glanzmann’s thrombasthenia
Bibliographic record
Abstract
Man-Chiu PoonDepartments of Medicine, Pediatrics and Oncology and Southern Alberta Bleeding Disorders Clinic, University of Calgary and Calgary Health Region, Calgary, Alberta, CanadaAbstract: Glanzmann’s thrombasthenia (GT) is a congenital qualitative platelet disorders due to the deficiency or defect of platelet membrane GPIIb/IIIa (integrin αIIbβ3). The standard treatment for bleeding is platelet transfusion but repeated transfusion may result in the development of anti-platelet antibodies (to HLA and/or GPIIbIIIa) rendering future platelet transfusion ineffective. Alternative effective agent(s) are needed. There are increasing reports documenting efficacy of high dose rFVIIa in GT patients with adverse events uncommon. The efficacy is supported by evidence that high concentration FVIIa binds to activated platelet surface and improves thrombin generation to enhance deposition (adhesion) and aggregation of platelets lacking GPIIb/IIIa. While there are increasing clinical experiences, evidence-based clinical data are not available. There is a need for more clinical studies, particularly clinical trials, to further assess the efficacy, safety (particularly thrombotic events) and optimal regimen of rFVIIa in GT patients, either singly or in combination with other hemostatic agents such as platelet transfusion. In the absence of this data, for treatment of severe bleeding in GT patients with platelet antibodies and platelet refractoriness, rFVIIa at dose 90 μg/kg every 2 h for 3 or more doses could be considered. This more “optimal regimen” derived from a recent International Survey needs confirmation with larger studies. What the optimal regimen for surgical coverage is remains unresolved.Keywords: Glanzmann’s thrombasthenia, recombinant human activated factor VII (rFVIIa), bleeding, surgery, platelet transfusion, GPIIb/IIIa
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".