Epidural Hematoma Treated Conservatively: When to Expect the Worst
Bibliographic record
Abstract
BACKGROUND: The Brain Trauma Foundation's 2006 surgical guidelines have objectively defined the epidural hematoma (EDH) patients who can be treated conservatively. Since then, the literature has not provided adequate clues to identify patients who are at higher risk for EDH progression (EDHP) and conversion to surgical therapy. The goal of our study was to identify those patients. METHODS: We carried a retrospective review over a 5-year period of all EDH who were initially triaged for conservative management. Demographic data, injury severity and history, neurological status, use of anticoagulants or anti-platelets, radiological parameters, conversion to surgery and its timing, and Glasgow Outcome Scale were analyzed. Bivariate association and further logistic regression were used to point out the significant predictors of EDHP and conversion to surgery. RESULTS: 125 patients (75% of all EDH) were included. The mean age was 39.1 years. The brain injury was mild in 62.4% of our sample and severe in 14.4%. Only 11.2% of the patients required surgery. Statistical comparison showed that younger age (p< 0.0001) and coagulopathy (p=0.009) were the only significant factors for conversion to surgery. There was no difference in outcomes between patients who had EDHP and those who did not. CONCLUSIONS: Most traumatic EDH are not surgical at presentation. The rate of conversion to surgery is low. Significant predictors of EDHP are coagulopathy and younger age. These patients need closer observation because of a higher risk of EDHP. Outcome of surgical conversion was similar to successful conservative management.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| 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".