Abstract

The use of surface electromyography (sEMG) to identify subjects with chronic temporomandibular disorders (TMD) is controversial. The main objective of this study is to determine the diagnostic accuracy of EMG to differentiate between healthy subjects and those with TMD.This study evaluated 53 individuals with TMD who were referred to the university service and who fulfilled the eligibility criteria during the period of the study. Thirty-eight dental students were also recruited satisfying same eligibility criteria but without TMD. The inclusion criteria were to be fully dentate, have normal occlusion, and be righthanded. The exclusion criteria were periodontal pathology, caries or damaged dental tissues, orthodontic therapy, maxillofacial disease, botulinum A toxin therapy, and psychological disorders.The means of the masseter muscles, right (RM) and left (LM), and temporalis muscles, right (RT) and left (LT), and intraindividual indexes during resting and during clenching were calculated. Raw sEMG activity was used to determine the cutoff points and calculate the diagnostic accuracy of sEMG. The diagnostic accuracy of these variables for a diagnosis of TMD was evaluated by using the Receiver Operating Characteristic (ROC) curve and the area under it (AUC). A new transformed diagnostic variable was obtained by using the Generalized Additive Models (GAM). Optimal cutoff points were obtained where the sensitivity and specificity were similar and by the Youden index. The highest estimated AUC was 0.660 (95% CI 0.605–0.871) corresponding to the rLT variable during rest. When rLT and rACTIVITY (differences divided by sums of temporalis versus masseter muscles) were considered as a linear combination, the AUC increased to 0.742 (95% CI; 0.783–0.934).In conclusion, the raw sEMG evaluation of rest provided moderate sensitivity and specificity to discriminate between healthy individuals and those with TMD. The use of the indexes (mainly assessing the dominance of temporalis over masseter muscles during rest) is strongly recommended to increase the discriminatory capacity of raw sEMG evaluation.

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