Assessment of orofacial motor functions in TMD patients over the course of treatment with a modified occlusal splint
Bibliographic record
Abstract
Background. Temporomandibular disorders (TMD) significantly affect patients’ quality of life due to impaired orofacial motor functions, including chewing, swallowing, speech, and facial expressions. The assessment of treatment dynamics should rely on quantitative, objective data, such as surface electromyography (EMG), which allows the evaluation of muscle activity and coordination during various functional tasks. Objective: to study orofacial motor functions in patients with TMD through the quantitative analysis of interference EMG signals in the masticatory and temporal muscles, to calculate relevant indices, and to describe changes in muscle activity during chewing before and after treatment with a modified occlusal splint. Materials and methods. From 325 examined individuals, 85 patients (63 females (74 %) and 22 males (26 %), mean age 36.2 ± 10.8 years) with TMD were selected for analysis by randomization. All patients were divided into three groups based on the DC/TMD classification. Symptoms of physical pain and TMD were evaluated through questionnaires. The functional state of the muscles was assessed using electromyography. Statistical evaluation of the results was conducted with ANOVA and non-parametric Kruskal-Wallis and Wilcoxon tests. Results. Before treatment, orofacial motor control in TMD patients was impaired: in group II (myalgias), the Functional Activity Index (FI ATTIV) was –13.9 ± 4.8 %; in group III (combined pathologies), –6.8 ± 3.5 %, whereas in group I (disk disorders), partial preservation of masticatory muscle activity was observed (8.3 ± 5.9 %). Muscle overload on the balancing side was observed before treatment: As dextra in group I was 139.0 ± 30.7 %, in group II, 102.7 ± 15.9 %, in group III, 127.6 ± 22.9 %; As sinistra in group I was 122.8 ± 19.7 %, in group II, 124.3 ± 20.9 %, in group III, 130.5 ± 19.6 %. Post-treatment, FI ATTIV showed significant improvements: in group I, 7.0 ± 3.1 % (p > 0.05), in group II, 6.3 ± 2.4 % (p = 0.027), and in group III, 5.7 ± 3.4 % (p = 0.046). The asymmetry index (As, %) also demonstrated notable improvements: As dextra in group II reached 152.4 ± 31.2 % (p = 0.019) and in group III, 173.5 ± 37.4 % (p = 0.021); As sinistra in group II was 156.5 ± 33.8 % (p = 0.026) and in group III, 154.8 ± 21.5 % (p = 0.014). Conclusions. Quantitative EMG analysis showed that treatment with a modified occlusal splint effectively improves muscle balance, restores coordination between the working and balancing sides, and reduces pain in TMD patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".