Approaches Towards Treating Temporomandibular Joint Ankylosis: Experience With 27 Cases
Bibliographic record
Abstract
Objective: To analyze various modalities used in the surgical treatment of temporomandibular joint ankyloses at a tertiary care teaching hospital in Pakistan. Study design: Case series (retrospective). Settings: Oral and Maxillofacial Surgery department, Dental section, Faisalabad Medical University, Faisalabad-Pakistan. Duration: January 2012 to December 2016. Materials and methods: Twenty-seven patients who presented with TMJ ankylosis were operated in these five years. The ankyloses were classified using the Sawheney’s classification of TMJ ankylosis. Joints were exposed using Bramley Al Khayat and modified Blair incision in fresh cases while existing laceration was used in recurrent cases. Arthroplasty was carried out to restore mouth opening. The interpositioning was done using articular disc, temporalis muscle/fascia or silastic. The mouth opening exercises were initiated on the third post op day and the patients were followed regularly after the surgery. Results: Out of these 27 cases, 13 were male and 14 female (M:F 1:1.1). The age ranged from 02 years to 26 years with a mean age of 13.26+5.4 years. The average time for which the mouth opening remained restricted ranged from 01 year to 12 years with a mean of 5.96+2.8 years. Right side was affected in 11 cases and left side was involved in 9 cases while 07 were bilateral. 04 patients were classified as type I (14.8%), 10 type II (37%), 09 type III (33.3%) and 04 type IV (14.8%).Preoperative mouth opening ranged from 02mm to 15mm with a mean opening of 5.85+3.5 mm. Post-operative mouth opening ranged from 20mm to 40mm with a mean opening of 31+4.2 mm. T-test was used to compare pre-operative mouth opening with post-operative mouth opening and the results were found to be statistically significant (P-value > 0.05). Conclusion: Treating TMJ ankylosis is a challenging task and there are various inherent difficulties in the procedure but with careful planning and meticulous surgical technique satisfactory results can be achieved which can improve the patient’s quality of life quite significantly.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".