Abstract WP253: Diagnostic Evaluation and Outcome of Cerebral Fat Embolism: Single Center Retrospective Review
Bibliographic record
Abstract
Introduction: Cerebral Fat Embolism (CFE) is an underappreciated complication of trauma and orthopedic surgery whose diagnosis is mostly based on clinical suspicion. The utility of diagnostic testing is poorly defined. Methods: Using discharge diagnosis codes and a stroke database at a Level 1 Trauma Center, we performed a retrospective chart review of diagnostic workup and outcome for CFE from 2005 to 2019. Among those with a diagnosis of systemic fat emboli syndrome after long-bone fracture, cerebral involvement was established based on altered mental status, retinal findings, brain MRI findings or a combination of these. This report focuses on those who had MRI, all of which had findings of CFE. Results: Forty patients with CFE were identified, comprising 0.3% of all patients admitted with long-bone fractures. Of these patients, the average age was 39 years (SD 22), 30 (75%) were men, 28 (70%) had hypoxemia, 2 (5%) had petechial rash, and 29 (73%) were comatose, including 16 (40%) following orthopedic surgery. Brain MRI findings of CFE included scattered diffusion-restriction (60%), confluent white-matter edema (33%) and diffuse petechial hemorrhage (30%), with 27% having multiple findings of CFE. Ophthalmologic evaluation revealed exudates or hemorrhage suggestive of Purtscher-like retinopathy in 20 (91%) of 22 patients examined. Transcranial doppler microembolic signals (MES) were detected in 17 (53%) of 32 patients examined and were associated with scattered diffusion-restriction on MRI (chi square, p =0.01). Twelve patients (30%) died before discharge, 15 (38%) were discharged to a nursing facility, 12 (30%) to a rehabilitation facility and 1 (3%) to home. After a mean of 5.4 months, 1 patient had died, 11 had severe disability and 16 had moderate disability or better. Conclusion: The diagnosis of CFE is complicated by unknown sensitivity of diagnostic modalities. Nonetheless, typical MRI and ophthalmologic findings can assist in diagnosis. MES are associated with scattered infarction on MRI, suggesting active disease. The outcome of patients with CFE is highly variable, and a better understanding of this potentially devastating disease will require studies with larger numbers of cases collected in a standard fashion at multiple trauma centers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".