Transverse sacral fractures: case series and literature review.
Bibliographic record
Abstract
OBJECTIVES: To report experience with transverse sacral fracture, an uncommon injury frequently associated with neurologic deficit, and to perform a meta-analysis of the literature in order to define the role of decompression for the management of sacral fractures. DESIGN: A review of 7 cases. SETTING: A university-affiliated tertiary care centre. PATIENTS: Seven patients with transverse fractures of the sacrum. The mean follow-up was 13 months. INTERVENTIONS: A review of the clinical data and a search of the literature for studies that reported on 4 or more patients with a transverse sacral fracture. MAIN OUTCOME MEASURES: Mechanism of injury, type of neurologic deficit and its management. RESULTS: The most common mechanism in the 7 study patients was a fall from a height. Six patients had neurologic deficits, mostly in the form of bowel or bladder disturbance. Five of these were treated with surgical decompression, and 4 of them had an improvement in neurologic function. The 7 original studies from the literature dealt with a total of 55 patients. As in the study patients, falls from a height and motor vehicle accidents predominated as the mechanisms of injury. In contrast to patients in this study, 20 of 48 patients in the literature review with neurologic deficits were treated conservatively. CONCLUSIONS: The outcomes in this study are similar to those reported in the literature. The place of surgical decompression for patients with neurologic deficit cannot be clearly determined from the evidence currently available.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 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".