Proposed Protocol for Orofacial Pain Assessment Prior to Orthodontic Treatment: An Expert-Informed Framework
Bibliographic record
Abstract
Background: Temporomandibular disorders (TMDs) are the most common source of non-dental orofacial pain, with peak prevalence during adolescence and young adulthood—the same age group when orthodontic treatment is typically initiated. Although orthodontics is not a proven cause of TMD, pre-existing dysfunction may be aggravated during treatment, creating clinical and medico-legal risks. Objective: This paper proposes a structured diagnostic questionnaire and scoring framework for pre-orthodontic TMD assessment. The protocol aims to enhance the early recognition of high-risk patients, facilitate interdisciplinary communication, and lay a foundation for systematic validation. Methods: The framework was developed through synthesis of international diagnostic criteria (DC/TMD), a targeted narrative review of the literature, and expert clinical input. Diagnostic categories were selected based on prevalence, impact on orthodontic outcomes, and medico-legal significance. Weighted scoring stratifies patients into three pathways: (1) proceed with orthodontics without concern, (2) proceed with monitoring, or (3) defer orthodontics until TMD is managed. Results: The proposed questionnaire is designed to address inconsistencies in the literature by applying standardized diagnostic items and objective thresholds (e.g., jaw opening < 38 mm) and structured follow-up intervals. Case scenarios illustrate how risk stratification guides decision-making. The questionnaire includes intra-articular and pain-related TMD entities such as disk displacement, degenerative joint disease, myalgia, myofascial pain, arthralgia, headache, and trismus. The framework provides orthodontists with defensible baseline documentation while supporting safe and individualized patient care. Conclusions: Inconsistent diagnostic frameworks, malocclusion classifications, and outcome measures have fragmented the evidence base in orthodontics and TMD. The framework aims to provide orthodontists with structured baseline documentation that may support clinical decision-making and medico-legal risk management. Validation studies are required to establish psychometric reliability and international applicability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".