Fractures of the acetabulum in patients aged 60 years and older
Bibliographic record
Abstract
Using a prospective database of 1309 displaced acetabular fractures gathered between 1980 and 2007, we calculated the annual mean age and annual incidence of elderly patients > 60 years of age presenting with these injuries. We compared the clinical details and patterns of fracture between patients > 60 years of age (study group) with those < 60 years (control group). We performed a detailed evaluation of the radiographs of the older group to determine the incidence of radiological characteristics which have been previously described as being associated with a poor patient outcome. In all, 235 patients were > 60 years of age and the remaining 1074 were < 60 years. The incidence of elderly patients with acetabular fractures increased by 2.4-fold between the first half of the study period and the second half (10% (62) vs 24% (174), p < 0.001). Fractures characterised by displacement of the anterior column were significantly more common in the elderly compared with the younger patients (64% (150) vs 43% (462), respectively, p < 0.001). Common radiological features of the fractures in the study group included a separate quadrilateral-plate component (50.8% (58)) and roof impaction (40% (46)) in the anterior fractures, and comminution (44% (30)) and marginal impaction (38% (26)) in posterior-wall fractures. The proportion of elderly patients presenting with acetabular fractures increased during the 27-year period. The older patients had a different distribution of fracture pattern than the younger patients, and often had radiological features which have been shown in other studies to be predictive of a poor outcome.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".