The epidemiology of surgically treated acute subdural and epidural hematomas in patients with head injuries: a population-based study.
Bibliographic record
Abstract
BACKGROUND: The purpose of this paper is to review the population-based epidemiology of surgically treated post-traumatic epidural hematomas (EDHs) and/or subdural hematomas (SDHs) among patients who presented to the single neurosurgical centre in Nova Scotia. METHODS: We included all patients aged 16 years or older who presented to the tertiary care hospital with acute post-traumatic EDHs and/or SDHs between May 23, 1996, and May 22, 2005, and who were surgically treated. We generated an initial cohort from the provincial trauma registry and reviewed a total of 152 charts for possible inclusion; 70 (46%) patients met the study criteria. We performed a blinded, explicit chart review using a standardized data collection form, and we generated descriptive statistics. RESULTS: Of the patients who had surgery, 34 (49%) presented with SDHs, 23 (33%) presented with EDHs and 13 (19%) presented with both conditions. The median age was 45 years, and 80% of the cohort was male. The major mechanisms of injury were falls (51%), motor vehicle collisions (30%) and assault (11%). More than half (61%) of patients were transferred from referring hospitals while the remainder (39%) arrived directly without an intermediate facility. There were 18 postoperative deaths (26%). Forty-four of 70 patients (63%) had associated good outcomes at 6 months (Glasgow Outcome Scale). CONCLUSION: Acute post-traumatic EDHs and/or SDHs are relatively rare (0.83/100,000 population per annum) and are generally associated with good outcomes. Death was more likely among older, more severely injured patients and among those who required surgery for SDH rather than EDH.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".