Study Objectives:

To evaluate facial 3D stereophotogrammetry's effectiveness as a screening tool for pediatric obstructive sleep apnea (OSA) when used by dental specialists.

Methods:

One hundred forty-four subjects aged 2-17 years, including children fully diagnosed with pediatric OSA through nocturnal polysomnography (nPSG) or at high- or low-risk of pediatric OSA, participated in this study. 3D stereophotogrammetry, Craniofacial Index (CFI) and Pediatric Sleep Questionnaire (PSQ) were obtained from all participants. Ten dental specialists with interest in pediatric sleep breathing disorders classified OSA severity twice. Once, based only on 3D stereophotogrammetry, and then based on 3D stereophotogrammetry, CFI and PSQ. Intra-rater and inter-rater reliability, and diagnostic accuracy of pediatric OSA classification, were calculated. A cluster analysis was performed to identify potential homogeneous pediatric OSA groups based on their craniofacial features classified through the CFI.

Results:

Intra-rater and inter-rater agreement suggested a poor reproducibility when only 3D facial stereophotogrammetry was used and when all tools were assessed simultaneously. Sensitivity and specificity varied among clinicians, indicating a low screening ability for both 3D facial stereophotogrammetry, ranging 0.36-0.90, and 0.10-0.70, and all tools ranging 0.53-1.0 and 0.01-0.49, respectively. A high arched palate and reversed or increased overjet contributed to explaining how participating dental clinicians classified pediatric OSA.

Conclusions:

3D stereophotogrammetry-based facial analysis does not seem predictive for pediatric OSA screening, alone or combined with PSQ and CFI, when used by dental specialists interested in SDB. Some craniofacial traits, more specifically significant sagittal overjet discrepancies and an arched palate, seem to influence participating dental specialist's classification.

中文翻译：

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牙科专家使用面部立体摄影作为小儿阻塞性睡眠呼吸暂停的筛查工具

学习目标：

评估面部 3D 立体摄影测量法作为牙科专家使用的小儿阻塞性睡眠呼吸暂停 (OSA) 筛查工具的有效性。

方法：

144 名年龄在 2-17 岁之间的受试者参与了这项研究，包括通过夜间多导睡眠图 (nPSG) 完全诊断为小儿 OSA 或小儿 OSA 高风险或低风险的儿童。从所有参与者获得 3D 立体摄影测量、颅面指数 (CFI) 和小儿睡眠问卷 (PSQ)。十位对儿科睡眠呼吸障碍感兴趣的牙科专家对 OSA 的严重程度进行了两次分类。曾经，仅基于 3D 立体摄影测量，然后基于 3D 立体摄影测量、CFI 和 PSQ。计算了评估者内部和评估者之间的可靠性，以及儿科 OSA 分类的诊断准确性。进行了聚类分析，以根据通过 CFI 分类的颅面特征识别潜在的同质儿科 OSA 组。

结果：

当仅使用 3D 面部立体摄影测量法并且同时评估所有工具时，评估者内部和评估者之间的协议表明可重复性较差。临床医生的敏感性和特异性各不相同，表明 3D 面部立体摄影测量的筛选能力较低，范围为 0.36-0.90 和 0.10-0.70，所有工具的筛选能力分别为 0.53-1.0 和 0.01-0.49。上颚高弓和反覆或增加的覆盖有助于解释参与的牙科临床医生如何对儿科 OSA 进行分类。

结论：

当对 SDB 感兴趣的牙科专家使用时，基于 3D 立体摄影测量的面部分析似乎无法预测儿科 OSA 筛查，无论是单独使用还是与 PSQ 和 CFI 结合使用。一些颅面特征，更具体地说是显着的矢状面覆盖差异和拱形上颚，似乎会影响参与的牙科专家的分类。