The Use of Traction Methods to Correct Severe Cervical Deformity in Rheumatoid Arthritis Patients
Bibliographic record
Abstract
STUDY DESIGN: A case series is presented. OBJECTIVES: To describe the methods of correction used in this study for flexible severe cervical deformity, and to report the results in patients with rheumatoid arthritis. SUMMARY OF BACKGROUND DATA: Long-standing rheumatoid arthritis can lead to severe cervical deformity, causing significant functional deficits and poor cosmesis. Information on the use of traction combined with surgical stabilization to achieve correction of flexible deformity in rheumatoid patients is sparse in the English literature. METHODS: A review of five cases, including pertinent history, physical examination, radiographic evaluation, traction techniques, surgical stabilization, and outcomes, was conducted. RESULTS: Excellent correction of deformity and radiographic union were achieved in all the patients. One patient had minimal loss of correction after surgery and thereafter remained stable. Pin tract infections were the only significant complication. CONCLUSIONS: Severe cervical flexible deformity in rheumatoid patients can cause significant disability and can be treated successfully with a combination of traction techniques and surgical stabilization.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".