The temporal profile of the anti-PF4/heparin immune response
Bibliographic record
Abstract
The immune response in heparin-induced thrombocytopenia (HIT) is puzzling: heparin-naive patients can develop IgG antibodies and clinical HIT as early as day 5, and evidence for an anamnestic response on heparin reexposure is lacking. We assessed daily serum samples by anti-PF4/heparin enzyme-immunoassay (EIA) in patients receiving heparin thromboprophylaxis. Of 435 patients, 56.1% showed an increase in EIA optical density (OD) of more than or equal to 15%, with more than 90% starting between days 4 and 14. After reaching maximum reactivity by days 10 to 12, ODs declined despite heparin continuation, including in 2 patients with clinical HIT. Individual IgG/A/M classes showed identical time of onset (median, day 6). Most (58.7%) antibody-positive patients developed all 3 Ig classes; only 11.3% lacked IgG response. IgG/A/M increase usually occurred simultaneously (+/- 1 day) with no general tendency for IgM precedence. Consistent with the transient immune response, none of the IgG-EIA-positive (OD > 0.5) patients at discharge developed clinically evident thrombosis during extended low-molecular-weight heparin thromboprophylaxis. The rapid onset of the anti-PF4/heparin immune response, its transience, and the simultaneous appearance of antibodies of different classes with no IgM precedence suggest short-term activation of B cells that have previously undergone Ig-class switching even without previous pharmacologic heparin exposure.
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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 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".