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Respiratory and sleep characteristics based on frequency distribution of craniofacial skeletal patterns in Korean adult patients with obstructive sleep apnea

OBJECTIVE: To investigate the frequency distribution of various craniofacial skeletal patterns in a large Korean adult obstructive sleep apnea (OSA) population, and to find a relationship between craniofacial risks and respiratory and sleep characteristics. METHODS: A total of 1226 OSA patients (mea...

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Detalles Bibliográficos
Autores principales: Kim, Su-Jung, Ahn, Hyo-Won, Hwang, Kyoung Jin, Kim, Sung-Wan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371191/
https://www.ncbi.nlm.nih.gov/pubmed/32687512
http://dx.doi.org/10.1371/journal.pone.0236284
Descripción
Sumario:OBJECTIVE: To investigate the frequency distribution of various craniofacial skeletal patterns in a large Korean adult obstructive sleep apnea (OSA) population, and to find a relationship between craniofacial risks and respiratory and sleep characteristics. METHODS: A total of 1226 OSA patients (mean age of 44.9±13.3 years) were included in this retrospective cross-sectional study. All subjects were evaluated for gender and age using fourteen polysomnographic, five cephalometric, two comorbid variables, and three self-reported indexes. Frequency analysis was used to screen the distribution of main skeletal patterns and subtypes. Intergroup comparisons were performed using independent t-test, chi-square test or analysis of variance. Univariable regression analysis was done to find a relationship between skeletal risks and OSA characteristics. RESULTS: The frequency distribution of skeletal patterns was as follows: sagittally 57.2%, 32.3%, and 10.5% of Class II, Class I, and Cass III; vertically 54.0%, 26.7%, and 19.3% of hyperdivergent, normodivergent, and hypodivergent type, respectively. Polysomnographic, symptomatic, and comorbid variables showed no differences among patients with different skeletal patterns. Conversely, skeletal variables showed no differences according to OSA severity. The prevalence of highly risky skeletal pattern of hyperdivergent Class II was more likely to be females (OR 4.52, P < .01) and less obese (OR 3.21, P < .01), irrelevant to OSA and sleep characteristics. CONCLUSION: Characteristic frequency distributions of skeletal patterns and subtypes were observed in adult OSA patients however, no statistical association was found between the skeletal patterns and OSA characteristics due to the large interindividual variation.