A Single Center Study on Patient Outcomes Following Temporomandibular Joint Replacement Using a Single Patient-Specific TMJ Prosthesis: The Mount Sinai Hospital / University of Toronto Experience
Bibliographic record
Abstract
AbstractObjectives: Despite growing use of custom alloplastic TMJ prostheses, long-term device survivorship data and their effect on patient function for specific systems remain limited. This study aims to determine evaluate the 3-year survivorship of a single patient-matched TMJ implant system placed at a single tertiary center, evaluate functional patient outcomes and identify any patient-related predictors of revision. Patients and Methods: A retrospective review of custom Zimmer BiometTM total-TMJ replacements performed at Mount Sinai Hospital (Jan 2004–Dec 2018) by a single operator captured demographics, primary diagnoses, functional outcomes, and any re-operations or device replacements. Results: 100 patients (80 women, 20 men; mean age = 43 years, range 16 to 70) underwent custom alloplastic TMJ reconstruction, receiving a combined total of 174 prostheses (74 bilateral, 26 unilateral), and were followed a mean of 5.1 ± 2.9 years (median = 3.7, maximum = 15.5). Pre-operative TMJ diagnoses were mainly osteoarthritis (79 %), ankylosis (29 %), inflammatory arthritides (10 %), and benign neoplasms (9 %), with trauma, revision, or developmental deformity accounting for the remainder (8 %). Almost half (47.5 %) had prior open-joint surgery, and 67 % underwent simultaneous orthognathic or other reconstructive procedures at time implantation. Mouth opening (in millimeters) and pain levels (Numeric Rating Scale, NRS 0-10) significantly improved (p < 0.001) from baseline to both 1-year and 5-years postoperatively and remained stable between during that period. Conclusions: The 3-year survivorship of a single patient-matched TMJ implant system was 96%, which aligns with previously reported rates for other contemporary devices (94 to 96 %). accompanied by lasting pain relief and functional gains. A failure rate of 4 % was observed due to heterotopic bone formation, infection, malocclusion, or dislocation, which reflects patterns observed in other studies. No patient- or surgery-level predictors emerged, likely due to the few events reported. The limited follow-up period of 3 years and absence of stock-implant controls reflects only early implant performance, while limiting implant generalizability and ability to draw any implant-specific conclusions. Future multi-centre, large-scale studies with long-term surveillance, i.e. ≥10-year, should focus on stratifying outcomes by primary TMJ diagnosis, patient comorbidities, and prior surgery, to further assist in developing validated risk-assessment tools, and evaluate modifiable factors, such as patient selection, surgical planning, and post-operative rehabilitation to further reduce failure rate and optimize functional recovery.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".