P.038 Bilateral carotid thrombi and cerebral infarction as a manifestation of heparin-induced thrombocytopenia with normal platelet count: a case report
Bibliographic record
Abstract
Background: This is the first report of Heparin induced thrombocytopenia (HIT) presenting as bilateral carotid thrombi and multiple cerebral infarcts. Methods: 54 year old woman presented with sudden onset of right arm numbness and weakness two days after discharge from hospital. During her hospitalization 9 days prior, she underwent colovesicular fistula repair, received heparin subcutaneously for DVT prophylaxis and had normal platelet counts. Results: On this admission, MRI Brain showed scattered multiple acute infarcts within the cortex of bilateral cerebral hemispheres. CT angiography head /neck showed non-occlusive thrombi at the carotid bifurcations bilaterally. Platelet count on admission was 267 K/uL q which decreased to 125 K/uL the next day, after which heparin was started for the carotid thrombi. The platelet count rapidly decreased further to 79 K/uL leading to suspicion for HIT and switching to Argatroban. HIT and serotonin release assay were positive confirming the diagnosis of HIT. CT chest and tranthoracic echocardiogram was normal. Venous Duplex of bilateral upper and lower extremities were negative for DVTs.Hypercoaguable evaluation was negative. Conclusions: This case highlights the importance of identifying HIT as a cause of arterial thrombosis and stroke even with normal platelet counts in the clinical setting of recent heparin use.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".