School of Dentistry, Faculty of Medicine and Dentistry, College of Health Sciences, University of Alberta, Edmonton, Alberta, Canada.
Department of Mathematical and Statistical Sciences, Faculty of Sciences, College of Sciences, University of Alberta, Edmonton, Alberta, Canada.
J Clin Sleep Med. 2023 Nov 1;19(11):1857-1865. doi: 10.5664/jcsm.10694.
We conducted this study to identify phenotypes of obstructive sleep apnea (OSA) in children based on lifestyle, sleep habits, age, obesity, sex, soft tissue facial features, and specific craniofacial abnormalities.
Seventy-three children with symptoms of pediatric OSA who underwent overnight observed polysomnography participated in this study. Soft tissue facial features were assessed using a 3-dimensional stereophotogrammetric system. Craniofacial abnormalities were evaluated based on the most common facial features associated with orthodontic treatment needs. Data regarding lifestyle, sleep habits, age, obesity, and sex were also collected. To identify phenotypes of OSA, a sequential analysis was then performed on categories of variables using fuzzy clustering with medoids.
Craniofacial abnormalities and soft tissue facial features defined clusters. Three clusters were identified. Cluster 1 comprised a group of younger children (5.9 ± 3.8 years) without obesity, without craniofacial abnormalities, and with smaller soft tissue facial features dimensions. Cluster 2 comprised a group of older children (9.6 ± 3.9 years) without obesity and with larger mandibular dimensions and mildly arched palates (71.4%). Cluster 3 comprised a group of older children (9.2 ± 3.9 years) with obesity and a history of health issues (68.4%), excessive lower facial height (63.2%), and midface deficiency (73.7%). No differences were observed across clusters regarding sleep features. A moderate severity of obstructive and mixed respiratory events was observed in all 3 clusters.
The study results did not identify distinct phenotypes of pediatric OSA based on soft tissue facial features or craniofacial abnormalities alone. Age and body mass index likely modify the effect of soft tissue facial features and craniofacial abnormalities as risk factors for OSA in children.
Fernandes Fagundes NC, Loliencar P, MacLean JE, Flores-Mir C, Heo G. Characterization of craniofacial-based clinical phenotypes in children with suspected obstructive sleep apnea. . 2023;19(11):1857-1865.
本研究旨在基于生活方式、睡眠习惯、年龄、肥胖、性别、软组织面部特征和特定的颅面畸形，确定儿童阻塞性睡眠呼吸暂停（OSA）的表型。
本研究纳入了 73 例有小儿 OSA 症状并接受过夜观察性多导睡眠图检查的患儿。使用三维立体摄影测量系统评估软组织面部特征。根据与正畸治疗需求相关的最常见面部特征评估颅面畸形。还收集了有关生活方式、睡眠习惯、年龄、肥胖和性别的数据。为了确定 OSA 的表型，然后使用聚类中位数的模糊聚类对变量类别进行顺序分析。
颅面畸形和软组织面部特征定义了聚类。确定了 3 个聚类。聚类 1 由一组年龄较小的儿童（5.9±3.8 岁）组成，他们没有肥胖，没有颅面畸形，软组织面部特征尺寸较小。聚类 2 由一组年龄较大的儿童（9.6±3.9 岁）组成，他们没有肥胖，下颌骨尺寸较大，腭弓轻度拱形（71.4%）。聚类 3 由一组年龄较大的儿童（9.2±3.9 岁）组成，他们肥胖且有健康问题史（68.4%），下脸部高度过度（63.2%）和中面部发育不足（73.7%）。三个聚类在睡眠特征方面没有差异。所有 3 个聚类均观察到中度阻塞性和混合性呼吸事件。
研究结果表明，仅根据软组织面部特征或颅面畸形无法确定小儿 OSA 的明确表型。年龄和体重指数可能会改变软组织面部特征和颅面畸形作为儿童 OSA 危险因素的作用。
Fernandes Fagundes NC, Loliencar P, MacLean JE, Flores-Mir C, Heo G. Characterization of craniofacial-based clinical phenotypes in children with suspected obstructive sleep apnea.. 2023;19(11):1857-1865.
