Assessment of the effects of physiotherapy in patients with bruxism with the use of splint therapy – preliminary study
Bibliographic record
Abstract
Background: Bruxism is an increasingly prevalent phenomenon that adversely impacts the masticatory system, often being associated with temporomandibular joint disorders.Dental physiotherapy primarily addresses dysfunctions within the temporomandibular joint, as well as pathology within the cervical section and muscles in the craniofacial region, including the supra and infrahyoid muscles.Aims: This study aimed to compare the effects of dental physiotherapy between two groups of patients with bruxism, with one group receiving additional treatment using a Michigan relaxation splint. Material and methods:The study included twenty participants, with one group (n=10) undergoing dental physiotherapy alone (G1), and the second group (n=10) receiving dental physiotherapy along with Michigan relaxation splints (G2).The therapy cycle comprised a total of six visits, occurring twice a week.Therapeutic interventions encompassed fascial work on the face, cervical, sternum, and thorax; deep tissue massage; trigger point development; and post-isometric muscle relaxation.Additionally, patients engaged in the Rocabado exercise program at home.Results: Therapy resulted in significant improvements in active cervical mobility for both groups across various movements (p<0.05), with no statistically significant differences observed between the two groups after therapy (p>0.05).Also, therapy led to significant improvements in mandibular movements for both Key wordsbruxism, soft tissue therapy, dental physiotherapy, relaxation splint. Physiotherapy Review | Volume XXVIII Issue 1/2024groups across various dimensions (p<0.05).There were no statistically significant differences between the two groups after therapy in terms of mandibular abduction, protrusion, and lateral movements (p>0.05).In both groups, a significant reduction in pain was achieved after the therapy (G1 p=0.0051;G2 p=0.0051).In both groups, the number of trigger points and associated pain was significantly reduced after the therapy (p<0.05).Conclusions: Physiotherapeutic procedures, involving soft tissue work and the incorporation of Rocabado exercises, demonstrated a substantial capacity to enhance the active range of motion (ROM) of the cervical and mandibular regions.Furthermore, these interventions contributed to pain reduction and a decrease in the number of trigger points in patients with bruxism.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".