Treatment of Injuries to the Subaxial Cervical Spine: Recommendations of the Spine Section of the German Society for Orthopaedics and Trauma (DGOU)
Bibliographic record
Abstract
STUDY DESIGN: Expert consensus. OBJECTIVES: To establish treatment recommendations for subaxial cervical spine injuries based on current literature and the knowledge of the Spine Section of the German Society for Orthopaedics and Trauma. METHODS: This recommendation summarizes the knowledge of the Spine Section of the German Society for Orthopaedics and Trauma. RESULTS: Therapeutic goals are a stable, painless cervical spine and protection against secondary neurologic damage while retaining maximum possible motion and spinal profile. The AOSpine classification for subaxial cervical injuries is recommended. The Canadian C-Spine Rule is recommended to decide on the need for imaging. Computed tomography is the favoured modality. Conventional x-ray is preserved for cases lacking a "dangerous mechanism of injury." Magnetic resonance imaging is recommended in case of unexplained neurologic deficit, prior to closed reduction and to exclude disco-ligamentous injuries. Computed tomography angiography is recommended in high-grade facet joint injuries or in the presence of vertebra-basilar symptoms. A0-, A1- and A2-injuries are treated conservatively, but have to be monitored for progressive kyphosis. A3 injuries are operated in the majority of cases. A4- and B- and C-type injuries are treated surgically. Most injuries can be treated with anterior plate stabilization and interbody support; A4 fractures need vertebral body replacement. In certain cases, additive or pure posterior instrumentation is needed. Usually, lateral mass screws suffice. A navigation system is advised for pedicle screws from C3 to C6. CONCLUSIONS: These recommendations provide a framework for the treatment of subaxial cervical spine Injuries. They give advice about diagnostic measures and the therapeutic strategy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".