Comparison of Mortality Following Hospitalisation for Isolated Head Injury in England and Wales, and Victoria, Australia
Bibliographic record
Abstract
BACKGROUND: Traumatic brain injury (TBI) remains a leading cause of death and disability. The National Institute for Health and Clinical Excellence (NICE) guidelines recommend transfer of severe TBI cases to neurosurgical centres, irrespective of the need for neurosurgery. This observational study investigated the risk-adjusted mortality of isolated TBI admissions in England/Wales, and Victoria, Australia, and the impact of neurosurgical centre management on outcomes. METHODS: Isolated TBI admissions (>15 years, July 2005-June 2006) were extracted from the hospital discharge datasets for both jurisdictions. Severe isolated TBI (AIS severity >3) admissions were provided by the Trauma Audit and Research Network (TARN) and Victorian State Trauma Registry (VSTR) for England/Wales, and Victoria, respectively. Multivariable logistic regression was used to compare risk-adjusted mortality between jurisdictions. FINDINGS: Mortality was 12% (749/6256) in England/Wales and 9% (91/1048) in Victoria for isolated TBI admissions. Adjusted odds of death in England/Wales were higher compared to Victoria overall (OR 2.0, 95% CI: 1.6, 2.5), and for cases <65 years (OR 2.36, 95% CI: 1.51, 3.69). For severe TBI, mortality was 23% (133/575) for TARN and 20% (68/346) for VSTR, with 72% of TARN and 86% of VSTR cases managed at a neurosurgical centre. The adjusted mortality odds for severe TBI cases in TARN were higher compared to the VSTR (OR 1.45, 95% CI: 0.96, 2.19), but particularly for cases <65 years (OR 2.04, 95% CI: 1.07, 3.90). Neurosurgical centre management modified the effect overall (OR 1.12, 95% CI: 0.73, 1.74) and for cases <65 years (OR 1.53, 95% CI: 0.77, 3.03). CONCLUSION: The risk-adjusted odds of mortality for all isolated TBI admissions, and severe TBI cases, were higher in England/Wales when compared to Victoria. The lower percentage of cases managed at neurosurgical centres in England and Wales was an explanatory factor, supporting the changes made to the NICE guidelines.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".