Effect of fondaparinux on platelet activation in the presence of heparin-dependent antibodies: a blinded comparative multicenter study with unfractionated heparin
Bibliographic record
Abstract
Heparin-induced thrombocytopenia (HIT) is a complication of heparin therapy caused by antibodies against a complex of platelet factor 4 and heparin. Fondaparinux (Arixtra) is a new synthetic selective factor Xa inhibitor. We performed a serologic study to determine the cross-reactivity of HIT sera with fondaparinux. Using a prospective, blinded study design, 39 clinically and serologically confirmed sera from patients with HIT and 15 control sera were sent to 3 different laboratories, each of which specialized in a particular HIT assay. These include the serotonin release assay, heparin-induced platelet agglutination assay, and platelet aggregation assay. Two of 82 assays (2.4%) performed in the presence of control sera were positive, both with unfractionated heparin. In the presence of HIT sera, 75 of 94 (79.8%) evaluable assays were positive with unfractionated heparin; fondaparinux was significantly (P < .001) less reactive than unfractionated heparin, only 3 of 91 evaluable assays (3.3%) being positive. Using flow cytometry, unlike unfractionated heparin, fondaparinux did not induce the binding of PAC1 and anti-CD62 monoclonal antibodies or of annexin V to platelets with HIT sera. Together, these results suggest that fondaparinux is nonreactive to HIT sera and raise the possibility that the drug may be used for prophylaxis and treatment of thrombosis in patients with a history of HIT.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".