Occlusion, jaw function and nocturnal muscle tone in obstructive sleep apnea with and without sleep bruxism

Abstract

Objectives: Sleep bruxism (SB) is highly prevalent among patients with obstructive sleep apnea (OSA), yet its etiology remains unclear. This prospective clinical trial aimed to evaluate the diagnostic relevance of occlusion, jaw function, and electromyographic (EMG) muscle tone in OSA patients with and without SB.

Materials and methods: A total of 105 OSA patients (74 males, 31 females; mean age: 56.1 ± 11.4 years) were assessed, including those with SB and without SB (NSB). Evaluations included occlusal parameters, the Jaw Functional Limitation Scale (JFLS-20), and polysomnography with EMG muscle tone analysis. Descriptive statistics, inter-group comparisons, Spearman's correlation analyses, and Receiver Operating Characteristic (ROC) curve analyses were performed.

Results: No significant differences in occlusal parameters were observed between the SB and NSB groups. However, SB patients exhibited significantly higher JFLS-20 scores compared to NSB patients (P = 0.002; mean global score: 20.79 ± 31.96 vs. 6.52 ± 9.70). EMG muscle tone showed significant correlations with JFLS mobility (P = 0.015) and overall jaw function (P = 0.046). ROC curve analysis for EMG muscle tone revealed an Area Under the Curve (AUC) of 0.911 (P < 0.001). An optimal cutoff value of 9.79 µV for EMG muscle tone demonstrated a sensitivity of 78.6% and specificity of 87.9%.

Conclusion: EMG muscle tone may serve as a preliminary reference point for differentiating SB from NSB in OSA patients, whereas occlusion lacks diagnostic significance.

Clinical relevance: These findings highlight the importance of incorporating functional assessments into the diagnostic workflow for SB in OSA patients. Therapeutic strategies should prioritize functional management rather than occlusal corrections.

Keywords: Electromyography; Jaw function; Muscle tone; Obstructive sleep apnea; Occlusion; Sleep bruxism.

Fig. 1

Upper and lower envelopes of the masseter EMG were subtracted to calculate the EMG amplitude. EMG tone values (∅_1sec) were calculated by averaging the EMG amplitude within each 1-second interval. Mean muscle tone values were calculated subsequently for each sleep stages (N1-N3, REM) [24]

Fig. 2

Differences in jaw functional limitation (JFLS) subscales mastication, mobility, communication and the global score (JFLS-20) between sleep bruxism (SB: n = 39) and non-sleep bruxism (NSB: n = 66) patients. Data are shown as mean ± standard error of the mean (SEM). P value was performed using Mann-Whitney U tests

Fig. 3

Frequencies of dento-skeletal class I, class II.1, class II.2, class III between sleep bruxers (SB: n = 39) and no sleep bruxers (NSB: n = 66) and of the occlusal parameters lateral crossbite, increased overbite, increased overjet between both groups (SB: n = 39, NSB: n = 66). P value was performed using Fisher’s exact test

Fig. 4

Receiver Operating Characteristic (ROC) to select the best discriminant cut-off point of EMG muscle tone to classify between sleep bruxers and non-sleep bruxers

Fig. 5

Spearman correlation coefficient (rs) was calculated to measure linear correlations between jaw functional limitation (JFLS) subscales mastication, mobility, communication and the global score (JFLS-20) and mean EMG (electromyographic) muscle tone in µV in TST (total sleep time [minutes asleep in bed after “lights off”, considering only nighttime sleep]). The correlation is two-sided significant at the level of 0.05 (* P < 0.05)