Relationship between MRI, Arthroscopic and Clinical Findings in TMD: Our Experience in Manitoba
Bibliographic record
Abstract
Objectives: To study correlations between magnetic resonance imaging, arthroscopic and clinical findings in patients with temporomandibular joint disorders in Manitoba. Study Patients and Methods:A retrospective chart review was conducted on temporomandibular joint disorders patients who were diagnosed with MRI scan and treated with arthroscopic lysis and lavage at Health Sciences Centre and Seven Oaks General Hospital from 2006-2012.A data capture sheet collected clinical findings, disc position inferred from MRI scan and arthroscopic findings from patient records.The data was analyzed using the Minitab 15 Statistical Package.Results: Eighty-seven joints of 58 patients were evaluated with the average age of 36.9 years and mean follow up of 6 months.MRI showed 52% of joints with anterior disc displacement without reduction.Arthroscopic findings showed adhesions (88.5%), hyperemia (47.1%), and synovitis (31.0%) regardless of stages of internal derangement.There was a significant improvement in pain (P<0.05), and in the Interincisal Distance (IID) (from 29.2 mm to 34.4 mm) postoperatively. Conclusion:Although arthroscopic findings did not correlate with disc position as per MRI scan, arthroscopic lysis and lavage has significantly improved pain, and jaw range of motion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".