Management of heparin-induced thrombocytopenia
Bibliographic record
Abstract
PURPOSE OF REVIEW: The purpose of this review is to summarize recent findings on heparin-induced thrombocytopenia (HIT), a prothrombotic disorder caused by platelet-activating IgG targeting platelet factor 4 (PF4)/polyanion complexes. RECENT FINDINGS: HIT can explain unusual clinical events, including adrenal hemorrhages, arterial/intracardiac thrombosis, skin necrosis, anaphylactoid reactions, and disseminated intravascular coagulation. Sometimes, HIT begins/worsens after stopping heparin ('delayed-onset' HIT). Various HIT-mimicking disorders are recognized (e.g., acute disseminated intravascular coagulation/'shock liver' with limb ischemia). HIT has features of both B-cell and T-cell immune responses; uptake of PF4/heparin complexes into macrophages ('macropinocytosis') facilitates the anti-PF4/heparin immune response. Antibody-induced activation of monocytes and platelets via their FcγIIA receptors triggers an intense procoagulant response. Sometimes, HIT antibodies recognize PF4 bound to (platelet-associated) chondroitin sulfate, explaining how HIT might occur without concurrent or recent heparin (delayed-onset HIT, 'spontaneous HIT syndrome'). The molecular structure of HIT antigen(s) has been characterized, providing a rationale for future drug design to avoid HIT and improve its treatment. The poor correlation between partial thromboplastin time and plasma argatroban levels (risking subtherapeutic anticoagulation) and need for intravenous administration of argatroban have led to increasing 'off-label' treatment with fondaparinux or one of the direct oral anticoagulants. SUMMARY: Understanding the molecular mechanisms and unusual clinical features of HIT will improve its management.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".