ArticlePloS one2020
Respiratory and sleep characteristics based on frequency distribution of craniofacial skeletal patterns in Korean adult patients with obstructive sleep apnea.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Is Maxillomandibular Advancement Possible in Skeletal Class III Patients? A Scoping Review.Journal of clinical medicine · 2026Review
- Numerical simulation and functional evaluation of upper airway before and after twin block treatment with different respiratory pathways.Clinical oral investigations · 2025Article
- The Impact of Craniofacial Skeletal Patterns on Sleep Quality and Oral Health-Related Quality of Life Among Adults.Nature and science of sleep · 2025Article
- Three-dimensional assessment of the nasopharyngeal airway in Down syndrome during the mixed dentition period: a case-control study.The Angle orthodontist · 2025Article
- Relationship between Cephalometric and Ultrasonic Airway Parameters in Adults with High Risk of Obstructive Sleep Apnea.Journal of clinical medicine · 2024Article
- Sleep bruxism events: an epiphenomenon of severe obstructive sleep apnea?Clinical oral investigations · 2023Article
- Prevalence and effects of sleep-disordered breathing on middle-aged patients with sedative-free generalized anxiety disorder: A prospective case-control study.Frontiers in psychiatry · 2022Article
- The Link Between Obstructive Sleep Apnea and Orthodontic Anomalies in Obese Adult Population.Materia socio-medica · 2021Review
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Authors and funding
4 authors.
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Abstract
objectiveTo 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.
methodsA 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.
resultsThe 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.
conclusionCharacteristic 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.
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