Acta Stomatologica Croatica (Jan 2021)
Profiling of Patients with Temporomandibular Disorders: Experience of One Tertiary Care Center
Abstract
Objectives: The aim of this study was to assess typical and most prevalent characteristics of patients suffering from temporomandibular disorders (TMD) by a retrospective assessment of their medical records. Material and Methods: Demographic data and data on the characteristics of TMD were collected from the existing medical documentation of 304 TMD patients (250 females and 54 males) who had been referred to the Department of Dentistry, Clinical Hospital Center Zagreb from October 2016 to October 2020 due to temporomandibular pain. For the purpose of analysis, three age groups were formed: i) “children and adolescents” (up to 19 years of age); ii) “middle age” (from 20 to 50 years of age); iii) “older age” (>50 year- olds). A two-step cluster analysis was performed with the aim of classifying TMD patients into homogenous groups. Results: The mean age of patients whose data were included in the study was 33.8 ± 16.66, with a significantly higher age in the group of women (p<0.001). Most of the patients had chronic pain (67.4%), with the ratio in favor of chronic patients being significantly higher in women than in men (p=0.001). Data on parafunctional behavior were confirmed in 14.5% of patients. Data on the onset of symptoms during/just after orthodontic treatment were present in 14.5% of patients. Data on spontaneous pain, assessed with a visual analogue scale, were recorded in 87 patients, with a mean of 6.14 ± 1.79 and with the highest pain in the “older age” group. Physical therapy was the most common therapeutic modality (56.3%) followed by an occlusal splint (40.5%). The analysis revealed 5 different clusters in the TMD patient data set. Conclusions: Our results are largely in line with current epidemiological knowledge on TMD. Women predominated in all age groups and most of the patients experienced chronic pain. Classifying patients into homogeneous groups using the clustering method could provide better identification of subgroups of conditions that mainly occur together in these patients, thus providing the basis for more specific management.
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