Bibliographic record
Abstract
Atlantoaxial osteoarthritis (AAOA) is a clinical syndrome that consists of occipitocervical pain and cervical rotation limitation. Its clinical recognition is often deficient leading to misdiagnosis and suboptimal treatment. The incidence of AAOA varies from 5% in the sixth decade to as much as 18% in the ninth decade of life. Age, female sex, and excessive occupational cervical weight-bearing are the main risk factors for AAOA. Pain originates from the degeneration of the lateral C1-C2 joints and may be referred through the greater occipital nerve. Although AAOA is not easy to see on classic cervical spine views, the open mouth odontoid view has great diagnostic value. Magnetic resonance imaging, CT scan, and/or injections may be used for confirmatory testing. Initial treatment is conservative, including physiotherapy, pain medication, and imaging-guided injections. As many as two-thirds of patients improve with conservative treatment. Indication for surgery is incapacitating pain recalcitrant to nonoperative management. Surgeons' thorough knowledge of surgical anatomy and techniques is key for the notable clinical benefits expected with the surgery. New surgical technology helps C1-C2 fusion become safer and more reliable. This review aims to synthetize available data related to AAOA and to improve the understanding of this condition and its management in the orthopaedic community.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".