Anterior Reduction for Cervical Spine Dislocation
Bibliographic record
Abstract
In Brief Study Design. Retrospective analysis of a prospectively followed cohort. Objective. Long-term evaluation of patients with anterior stabilization for dislocations of the cervical spine. Setting. Level 1 trauma center. Summary of Background Data. Anterior stabilization of unstable cervical spine injuries is gaining popularity. However, the method of open reduction is controversial. Methods. Forty-one consecutive patients with unstable dislocations/subluxations of the subaxial cervical spine were included. Closed reduction was attempted in all patients using Gardner-Wells traction. If this failed, an anterior open reduction was performed. Tricortical iliac crest autograft and anterior plating was used. Patients were assessed for: 1) rate of successful reduction and stabilization using only the anterior surgical approach; and 2) complications and long-term clinical and radiologic outcome. Results. Two of eight (25%) anterior open reductions failed requiring posterior surgery. One of these patients had associated pedicle fractures with horizontal rotation of the lateral masses. All grafts had healed successfully at the most recent follow-up visit. Moderate neck discomfort was found in 5 of 41 patients. Significant neurologic improvement was observed. Conclusions. Most subluxations/dislocations of the subaxial cervical spine can be reduced using Gardner-Wells traction and successfully stabilized with anterior surgery alone. If closed reduction fails, anterior open reduction is successful in the majority of cases. This cohort study investigates the feasibility and outcome of the anterior approach for the management of cervical spine dislocations/subluxations in patients with variable neurologic deficits. Adherence to the described reduction maneuver leads to a successful outcome in the vast majority of cases.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".