Autoimmune heparin‐induced thrombocytopenia and venous limb gangrene after aortic dissection repair: in vitro and in vivo effects of intravenous immunoglobulin
Bibliographic record
Abstract
BACKGROUND: Heparin-induced thrombocytopenia (HIT) is a prothrombotic disorder characterized by heparin-dependent antibodies that activate platelets (PLTs) via PLT FcγIIa receptors. "Autoimmune" HIT (aHIT) indicates a HIT subset where thrombocytopenia progresses or persists despite stopping heparin; aHIT sera activate PLTs strongly even in the absence of heparin (heparin-independent PLT-activating properties). Affected patients are at risk of severe complications, including dual macro- and microvascular thrombosis leading to venous limb gangrene. High-dose intravenous immunoglobulin (IVIG) offers an approach to interrupt heparin-independent PLT-activating effects of aHIT antibodies. CASE REPORT: A 78-year-old male who underwent cardiopulmonary bypass for aortic dissection developed aHIT, disseminated intravascular coagulation, and deep vein thrombosis; progression to venous limb gangrene occurred during partial thromboplastin time (PTT)-adjusted bivalirudin infusion (underdosing from "PTT confounding"). Thrombocytopenia recovered with high-dose IVIG, although the PLT count increase began only after the third dose of a 5-day IVIG regimen (0.4 g/kg/day × 5 days). We reviewed case reports and case series of IVIG for treating HIT, focusing on various IVIG dosing regimens used. RESULTS: Patient serum-induced PLT activation was inhibited in vitro by IVIG in a dose-dependent fashion; inhibition of PLT activation by IVIG was much more marked in the absence of heparin versus the presence of heparin (0.2 U/mL). Our literature review indicated 1 g/kg × 2 IVIG dosing as most common for treating HIT, usually associated with rapid PLT count recovery. CONCLUSION: Our clinical and laboratory observations support dose-dependent efficacy of IVIG for decreasing PLT activation and thus correcting thrombocytopenia in aHIT. Our case experience and literature review suggests dosing of 1 g/kg IVIG × 2 for patients with severe aHIT.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".