Silent Disc Displacements vs. Noisy Normal Joints: Reassessing Clicking as a Marker of ADDwR
Bibliographic record
Abstract
Aim To evaluate the diagnostic value of temporomandibular joint (TMJ) clicking as a clinical marker of anterior disc displacement with reduction (ADDwR) by comparing clinical findings with magnetic resonance imaging (MRI). Material and method This retrospective study included 128 TMJ sides from adult patients referred for TMJ symptoms between January 2021 and December 2024. All patients underwent standardized clinical TMJ examination documenting the presence or absence of clicking, and bilateral 1.5T MRI with closed- and open-mouth sequences. Results Clinical examinations identified clicking in 114 of 128 joints (89.1%), while 14 joints (10.9%) were clinically silent. MRI demonstrated ADDwR in 112 joints (87.5%) and normal disc position in 16 joints (12.5%). Among ADDwR joints, 98 (87.5%) presented with clicking and 14 (12.5%) represented silent ADDwR. Of the 114 clicking joints, 98 (86.0%) had ADDwR and 16 (14.0%) had normal disc position, constituting clicking without displacement. Clicking showed high sensitivity for ADDwR (87.5%) but occurred in joints with normal disc position as well. Conclusion TMJ clicking is strongly associated with ADDwR but is neither exclusive to displaced discs nor universally present in reducible disc displacements. The coexistence of silent ADDwR and clicking in nondisplaced joints underscores the limitations of relying solely on auscultation or palpation and supports MRI as an important adjunct in diagnostically ambiguous cases.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".