Heparin-induced thrombocytopenia and thrombosis following subarachnoid hemorrhage
Bibliographic record
Abstract
The authors present a case of heparin-induced thrombocytopenia and thrombosis (HITT) that occurred after aneurysmal subarachnoid hemorrhage (SAH), and they review the relevant literature. An immune-mediated syndrome, HITT is characterized by moderate thrombocytopenia and paradoxical vascular thromboses. Although it has been estimated in prospective studies that HITT occurs in between 1 and 3% of patients receiving heparin, it is underrecognized in the neurosurgical literature. In the present case, a 49-year-old woman underwent clipping of a right posterior communicating artery aneurysm after suffering a Hunt and Hess Grade III SAH. She had an uncomplicated postoperative course with good clip positioning and no vasospasm observed on a cerebral angiogram obtained on Day 7. On Day 23, the patient developed a right hemiparesis and experienced a grand mal seizure. A head computerized tomography scan revealed a hemorrhagic infarct in the left middle cerebral artery distribution. Repeated cerebral angiograms did not show vasospasm. She was thrombocytopenic (platelet count as low as 46 x 10(9)/L on Day 28 compared with 213 x 10(9)/L on Day 1) and had been receiving heparin flushes to maintain intravenous catheter patency. An assay for HITT-associated antibodies was positive. The heparin flushes were discontinued and the platelet count recovered (121 x 10(9)/L). She improved neurologically, but was left with a significant right hemiparesis at discharge. This patient had assay-proven heparin-induced thrombocytopenia despite minimal exposure to heparin. Because there was no evidence of vasospasm or other factors to account for her delayed hemorrhagic infarction, an HITT-related disorder seemed most likely. Despite a large body of literature describing HITT in nonneurosurgical patients, only three previous neurosurgical cases have been published. This case report may serve to heighten awareness of this disorder.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".