Delayed onset of fat embolus in the cerebral venous system after breast and hip augmentation: a case report
Bibliographic record
Abstract
BACKGROUND: Cerebral fat embolism (CFE) is a subtype of fat embolism syndrome which tends to cause ischemic cerebral infarction. Fat embolism in the cerebral venous system have not been reported. We hereby present a rare case of fat embolus formed in the cerebral venous system 10 days after cosmetic surgery, and describe our management of this patient. CASE PRESENTATION: A 26-year-old woman with the disturbance of consciousness and recurrent convulsions of the right upper extremity over a 21-h period was admitted to our hospital. The patient was initially diagnosed with haemorrhagic infarction, and cerebral venous thrombosis (CVT) was suspected based on computed tomography (CT). A diagnosis of CFE was confirmed based on surgical findings. Breast and hip augmentation performed 10 days ago was considered the underlying cause. Drug-induced hypothermia, low molecular weight heparin, atorvastatin, dexamethasone, piperacillin/tazobactam, valproic acid, and mannitol were applied. On hospital day 30, she was discharged with a Montreal Cognitive Assessment score of 25. CONCLUSIONS: Fat embolism can occur in the cerebral venous system, and may mimic CVT symptoms rather than CFE symptoms. Early identification of the nature of the embolus is essential. The use of heparin may prevent secondary thrombus formation, and accelerate fat embolus decomposition.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| 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".