Mamede Isadora, Lacerda Sophia Paiva Silveira, Rodrigues Anna Bárbara Veloso Tomaz, Alvares Alice Veloso, Andrade Bruna Oliveira, Silva Bruna de Souza, Camargos Paulo, Martins Luciana Menezes Nogueira
Federal University of São João del Rei, Dona Lindu Campus, R. Sebastião Gonçalves Coelho, 400 - Chanadour, Divinópolis, MG, 35501-296, Brazil.
Federal University of Minas Gerais, Belo Horizonte, Brazil.
Sleep Breath. 2025 Jun 3;29(3):202. doi: 10.1007/s11325-025-03368-2.
Obstructive sleep apnea (OSA) disrupts breathing due to upper airway obstruction during sleep. This study presents the development of a mobile application for 2D craniofacial measurements associated with OSA, aiming to provide an accessible approach.
This single-center, cross-sectional, retrospective analysis utilized data from 128 patients who underwent polysomnography and facial photography. Craniofacial measurements were obtained using the mobile app and standard desktop software (Studio 3). Measurement reliability and agreement were assessed using the Intraclass Correlation Coefficient (ICC) and Bland-Altman analysis, with F-tests applied to ICCs.
The application showed good reliability for key measurements, including profile angle (ICC = 0.86, p < 0.01), nasolabial angle (ICC = 0.84, p < 0.01), neck angle (ICC = 0.88, p < 0.01), facial height (ICC = 0.73, p < 0.01), and facial width (ICC = 0.75, p < 0.01), with significant F-tests. Bland-Altman analysis corroborated these results. However, upper lip length (ICC = 0.42, p > 0.05) and lower lip length (ICC = 0.54, p > 0.05) showed lower reliability and non-significant F-tests. The mentolabial sulcus (ICC = 0.51, p = 0.04) exhibited moderate reliability but higher variability.
This mobile application shows promise as a reliable, accessible tool for OSA-related craniofacial assessment, especially useful in resource-limited settings. ICC and F-test values for primary measurements suggest the app's consistency with traditional methods, though the reduced reliability of lip length and mentolabial sulcus measurements may limit their clinical utility in individual assessments. Therefore, further refinements and validation in diverse populations are recommended.
阻塞性睡眠呼吸暂停（OSA）会在睡眠期间因上呼吸道阻塞而干扰呼吸。本研究展示了一款用于与OSA相关的二维颅面部测量的移动应用程序的开发，旨在提供一种便捷的方法。
这项单中心、横断面、回顾性分析使用了128例接受多导睡眠图检查和面部摄影患者的数据。使用移动应用程序和标准桌面软件（Studio 3）进行颅面部测量。使用组内相关系数（ICC）和Bland-Altman分析评估测量的可靠性和一致性，并对ICC应用F检验。
该应用程序对关键测量显示出良好的可靠性，包括侧脸角度（ICC = 0.86，p < 0.01）、鼻唇角（ICC = 0.84，p < 0.01）、颈角（ICC = 0.88，p < 0.01）、面部高度（ICC = 0.73，p < 0.01）和面部宽度（ICC = 0.75，p < 0.01），F检验具有显著性。Bland-Altman分析证实了这些结果。然而，上唇长度（ICC = 0.42，p > 0.05）和下唇长度（ICC = 0.54，p > 0.05）显示出较低的可靠性且F检验无显著性。颏唇沟（ICC = 0.51，p = 0.04）表现出中等可靠性但变异性较高。
这款移动应用程序有望成为一种可靠、便捷的工具，用于与OSA相关的颅面部评估，在资源有限的环境中尤其有用。主要测量的ICC和F检验值表明该应用程序与传统方法的一致性，尽管唇长度和颏唇沟测量的可靠性降低可能会限制它们在个体评估中的临床效用。因此，建议在不同人群中进行进一步的改进和验证。
