Influence of Symptom Longevity on Outcomes Following a Customized Rehabilitation Program for Painful Temporomandibular Disorders
Bibliographic record
Abstract
Purpose: To assess the impact of symptom longevity on functional outcomes, pain and patient perception of recovery following a rehabilitation program for temporomandibular disorders (TMDs) and to determine which variables were associated with improved function. Methods: Forty-eight patients who received TMD rehabilitation in an outpatient setting at a tertiary care facility were divided into acute, subacute and chronic groups based on symptom duration. A customized intervention program was developed for each patient according to assessment results and included the following interventions: manual therapy, neuromuscular re-education, orthotic and other modalities and self-management training. Functional indices, perceived pain and perceived improvement in the CareConnections Outcomes System were measured using a self-report questionnaire at initiation and completion of the therapy program. Results: Within each group, the average functional improvement score and pain score improved significantly from pre-treatment to post-treatment (p ≤ .05). Among the groups, no differences were noted for functional improvement, per cent decrease in pain and patient perception of improvement. In regression analyses, a model with initial pain intensity score (p = .002) and symptom longevity (p = .05) fit the data well and explained 25 per cent of the variance in functional outcome score. Conclusions: Patients with TMD showed improvements in function and pain after a customized rehabilitation program. Baseline pain scores and symptom longevity were highly associated with functional outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".