The Approach to Heparin-Induced Thrombocytopenia
Bibliographic record
Abstract
Heparin-induced thrombocytopenia (HIT) is a prothrombotic drug reaction caused by platelet-activating antibodies that recognize multimolecular complexes of platelet factor 4 (PF4) bound to heparin. HIT is an intense hypercoagulability state (increased thrombin generation in vivo) that is complicated more often by venous thromboembolism (deep vein thrombosis, pulmonary embolism) than by arterial thrombosis. HIT is a risk factor for coumarin-induced microthrombosis, particularly affecting acral regions of limbs with deep vein thrombosis (venous limb gangrene). Coumarins (e.g., warfarin) are therefore contraindicated during the acute (thrombocytopenic) phase of HIT. Venous thromboembolism can occur early during an episode of HIT, sometimes even before HIT-associated platelet count declines become clear. Recognition of HIT may be facilitated through the use of a clinical scoring system, the 4Ts ( Thrombocytopenia, Thrombosis, Timing, and o Ther explanations). Anti-PF4/polyanion enzyme-immunoassays (EIAs) and washed platelet activation assays readily detect HIT antibodies, and thus have high diagnostic sensitivity; however, only the platelet activation assays have high diagnostic specificity, suggesting that HIT is likely to be overdiagnosed in settings where EIAs are used exclusively for diagnosis. Treatment of HIT emphasizes substitution of heparin with an alternative nonheparin anticoagulant, such as a direct thrombin inhibitor (lepirudin, argatroban), or an indirect (antithrombin-mediated) inhibitor of factor Xa (danaparoid, fondaparinux?).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".