Pressure Algometry Evaluation of Two Occlusal Splint Designs in Bruxism Management-Randomized, Controlled Clinical Trial

Bartosz Dalewski, Agata Kamińska, Paweł Kiczmer, Krzysztof Węgrzyn, Łukasz Pałka, Katarzyna Janda, Ewa Sobolewska, Bartosz Dalewski, Agata Kamińska, Paweł Kiczmer, Krzysztof Węgrzyn, Łukasz Pałka, Katarzyna Janda, Ewa Sobolewska

Abstract

The aim of this pilot study was to evaluate the short-term effectiveness of two different occlusal devices and their impact on the pressure pain threshold (PPT) values among patients who reported to the Dental Prosthetics Outpatient Clinic of Pomeranian Medical University (Szczecin, Poland) and who were diagnosed with probable bruxism. Two groups were formed (A and B) to which patients were assigned randomly. Each group used a different occlusal splint for bruxism management. The occlusal appliance by Okeson, or the bimaxillary splint, was used overnight by each patient for 30 days of the study. The PPT was measured twice, at the first visit and after 30 days of using each occlusal device, with Wagner Paintest FPX 25 algometer. Bruxism was diagnosed based on data from the patient's medical history and from the physical examination. Nocturnal Bruxism Criteria according to the International Classification of Sleep Disorders (Third Edition) was used for the patient's evaluation. Results: similar pain factor (PF) reduction was observed in both the examined groups, regardless of the device used; canine guidance and no guidance were similarly effective in terms of increasing pain resilience.

Keywords: TMD; algometer; bruxism; canine guidance; clenching; grinding; masseter; masticatory muscle; occlusal appliance; pressure pain threshold; sleep disorder; splint; temporalis.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Wagner Paintest FPX 25.
Figure 2
Figure 2
PPT measurement points.
Figure 3
Figure 3
An occlusal appliance.
Figure 4
Figure 4
A bimaxillary splint.
Figure 5
Figure 5
Results of algometric measurements among the subjects presented as box and whiskers plot. A: MTAL algometric measurements, B: MTML algometric measurements, C: MTPL algometric measurements, D: TMJL algometric measurements, E: MOSL algometric measurements, F: MR algometric measurements, G: MTAR algometric measurements, H: MTMR algometric measurements, I: MTPR algometric measurements, A: TMJR algometric measurements, K: MOSP algometric measurements, L: Phalanx algometric measurements, M: C7 algometric measurements, N: ML algometric measurements. All data are presented as Mean +/− SD. Results of non parametric analysis for repeatable measurements (nparLD) are presented in the right corner of each plot.
Figure 5
Figure 5
Results of algometric measurements among the subjects presented as box and whiskers plot. A: MTAL algometric measurements, B: MTML algometric measurements, C: MTPL algometric measurements, D: TMJL algometric measurements, E: MOSL algometric measurements, F: MR algometric measurements, G: MTAR algometric measurements, H: MTMR algometric measurements, I: MTPR algometric measurements, A: TMJR algometric measurements, K: MOSP algometric measurements, L: Phalanx algometric measurements, M: C7 algometric measurements, N: ML algometric measurements. All data are presented as Mean +/− SD. Results of non parametric analysis for repeatable measurements (nparLD) are presented in the right corner of each plot.
Figure 6
Figure 6
Graphical interpretation of correlations between the algometric measurements grouped using hierarchical clustering (Pearson’s correlation coefficients presented in squares). More detailed correlations may be found in Figure 5.
Figure 7
Figure 7
Pain factor changes among groups during experiment.

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