High‐dose IVIG plus cangrelor platelet “anesthesia” during urgent heparin‐CPB in a patient with recent SRA‐negative HIT‐thrombosis with persisting platelet‐activating antibodies
Bibliographic record
Abstract
In a high-risk patient with subacute heparin-induced thrombocytopenia (HIT) type A (platelet count recovery following acute HIT but with persisting platelet-activating antibodies), in whom urgent cardiac surgery was required, a key clinical question arose: could intraoperative heparin be given safely with "platelet anesthesia" provided with high-dose intravenous immunoglobulin (IVIG) plus cangrelor (ultra-short-acting antiplatelet agent)? This approach proved successful, without unexpected postoperative thrombocytopenia or thromboembolism. In vitro studies confirmed that both IVIG and cangrelor contributed to perioperative inhibition of HIT antibody-induced platelet activation. Interestingly, despite the patient testing strongly positive in 4 HIT immunoassays (latex immunoturbidimetric assay and 3 enzyme-immunoassays), the serotonin-release assay (SRA) was consistently negative. Nevertheless, platelet-activating HIT antibodies were detectable using modified (platelet factor 4-enhanced) SRA. Our protocol of heparin rechallenge following IVIG/cangrelor provides both intraoperative and early postoperative inhibition of HIT antibody-induced platelet activation and is applicable to patients with circulating functional HIT antibodies requiring urgent heart surgery, including those with "SRA-negative HIT."
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| 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".