The object of this study was to analyze the oral health-related quality of life (OHRQoL) of patients with temporomandibular disorders (TMDs) who were treated simultaneously with ultrasound (US) and photobiomodulation therapy (PBMT). This study included 13 patients of both genders, with diagnosis of TMD according to the Research Diagnostic Criteria for Temporomandibular Disorders. The patients were treated with equipment consisting of US and PBMT in the same system. The treatment was applied to the left and right sides of the face in the masseter muscle, anterior temporalis muscle, and temporomandibular joint, two sessions per week for a total of eight sessions. The OHRQoL was assessed by the Oral Health Impact Profile (OHIP-14) at three moments: pretreatment (T), after the eight treatment sessions (T), and 30 days after termination of treatment (T). The Wilcoxon, Mann-Whitney , Kruskall-Wallis, and Spearman's correlation coefficient tests were applied, with a significance threshold of 5%. Psychological discomfort, physical pain, and psychological limitation were the domains where the highest scores were obtained at T. The total OHIP-14 scores at T and T were significantly lower than at T. No statistical differences were observed between T and T. We conclude that synergistic treatment was effective in improving the OHRQoL of patients with TMDs, and that its beneficial effects persisted at 1 month after termination of treatment.
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http://dx.doi.org/10.1089/photob.2019.4697 | DOI Listing |
Cureus
January 2025
College of Dentistry, King Saud University, Riyadh, SAU.
This research explores the types and effectiveness of occlusal splints in managing temporomandibular disorders (TMDs). TMDs encompass a range of musculoskeletal and neuromuscular conditions affecting the jaw, causing pain, limited movement, and discomfort. Occlusal splints, also known as bite guards, are commonly used in dentistry to alleviate TMD symptoms by relaxing jaw muscles, preventing joint trauma, and protecting teeth.
View Article and Find Full Text PDFJpn Dent Sci Rev
December 2025
Department of Orthodontics, College of Dentistry, University of Illinois at Chicago, Chicago, IL, USA.
This letter is being sent to editors of major dental journals around the world. Attached to it is an Announcement that summarizes a recently published position paper which deals with the topic of standards of care for Temporomandibular Disorders (TMDs). That paper, entitled "Temporomandibular disorders: INfORM/IADR key points for good clinical practice based on standard of care", was developed by a group of expert researchers and clinicians over a one-year period.
View Article and Find Full Text PDFJ Appl Oral Sci
January 2025
Shanghai Jiao Tong University School of Medicine, College of Stomatology, Shanghai Ninth People's Hospital, Department of Orthodontics, Shanghai, China.
Background: Past studies have indicated links between specific inflammatory proteins in the bloodstream and temporomandibular disorders (TMDs). Nonetheless, there remains the need for further solid research pinpointing the exact causes behind these associations. This Mendelian randomization (MR) study aims to examine the association between 91 circulating inflammatory proteins and TMDs.
View Article and Find Full Text PDFPurpose: The degenerative joint disease is a temporomandibular disorder. By analysing texture parameters, it becomes possible to characterize and differentiate various tissues, based on their textural properties according to cone-beam computed tomography (CBCT). This study evaluated degenerative diseases in the temporomandibular joint through texture analysis.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Orofacial Pain and Oral Medicine, Yonsei University College of Dentistry, 50-1, Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
This study aimed to develop an artificial intelligence (AI) model for the screening of degenerative joint disease (DJD) using temporomandibular joint (TMJ) panoramic radiography and joint noise data. A total of 2631 TMJ panoramic images were collected, resulting in a final dataset of 3908 images (2127 normal (N) and 1781 DJD (D)) after excluding indeterminate cases and errors. AI models using GoogleNet were evaluated with six different combinations of image data, clinician-detected crepitus, and patient-reported joint noise.
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