Bibliographic record
Abstract
Autoimmune thrombocytopenia (aHIT) is a severe subtype of heparin-induced thrombocytopenia (HIT) with atypical clinical features caused by highly pathological IgG antibodies ("aHIT antibodies") that activate platelets even in the absence of heparin. The clinical features of aHIT include: the onset or worsening of thrombocytopenia despite stopping heparin ("delayed-onset HIT"), thrombocytopenia persistence despite stopping heparin ("persisting" or "refractory HIT"), or triggered by small amounts of heparin (heparin "flush" HIT), most cases of fondaparinux-induced HIT, and patients with unusually severe HIT (e.g., multi-site or microvascular thrombosis, overt disseminated intravascular coagulation [DIC]). Special treatment approaches are required. For example, unlike classic HIT, heparin cessation does not result in de-escalation of antibody-induced hemostasis activation, and thus high-dose intravenous immunoglobulin (IVIG) may be indicated to interrupt aHIT-induced platelet activation; therapeutic plasma exchange may be required if high-dose IVIG is ineffective. Also, aHIT patients are at risk for treatment failure with (activated partial thromboplastin time [APTT]-adjusted) direct thrombin inhibitor (DTI) therapy (argatroban, bivalirudin), either because of APTT confounding (where aHIT-associated DIC and resulting APTT prolongation lead to systematic underdosing/interruption of DTI therapy) or because DTI inhibits thrombin-induced protein C activation. Most HIT laboratories do not test for aHIT antibodies, contributing to aHIT under-recognition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".