Camañes-Gonzalvo Sara, Montiel-Company José María, García-Selva Marina, Plaza-Espín Andrés, Pérez-Carbonell Tomàs, Paredes-Gallardo Vanessa, Bellot-Arcís Carlos, Marco-Pitarch Rocío
Sleep Unit, Department of Stomatology, Faculty of Medicine and Dentistry, University of Valencia, Valencia, Spain.
Department of Stomatology, Faculty of Medicine and Dentistry, University of Valencia, Valencia, Spain.
Orthod Craniofac Res. 2025 Jun;28(3):485-495. doi: 10.1111/ocr.12900. Epub 2025 Jan 24.
This non-randomised clinical study aimed to identify the phenotypic characteristics that distinguish responders from non-responders. Additionally, it sought to establish a predictive model for treatment response to obstructive sleep apnoea (OSA) using mandibular advancement devices (MAD), based on the analysed phenotypic characteristics.
This study, registered under identifier NCT05596825, prospectively analysed MAD treatment over 6 years using two-piece adjustable appliances according to a standardised protocol. Two response definitions aligned with the latest International Consensus Statement on OSA severity were established. Logistic regression and CHAID models integrated baseline clinical, anthropometric, cephalometric anatomical, soft tissue characteristics and physiological upper airway variables.
A total of 112 patients completed the study: 64 responders and 48 non-responders according to response definition 1, and 81 responders and 31 non-responders according to response definition 2. Responders to MAD treatment had lower body mass index (BMI), neck and waist circumference, Epworth Sleepiness Scale scores, apnoea-hypopnea index (AHI), snoring intensity on the Visual Analog Scale, CPAP pressure, and higher T90% and minSaO. Patients exhibiting greater anatomical imbalance, smaller airway volume, smaller minimum cross-sectional area (CSAmin) and longer airway length demonstrated a poorer response to treatment.
Airway length, initial T90% and anterior facial height collectively formed a highly predictive logistic regression model for response definition 1. Jarabak's ratio, gonial angle, CSAmin, airway length, initial BMI and baseline AHI constituted a highly predictive model for the second response definition. Furthermore, the CHAID regression tree established cutoff values for the variables that form the predictive models.
这项非随机临床研究旨在确定区分反应者与无反应者的表型特征。此外，该研究试图基于分析出的表型特征，建立一个使用下颌前移装置（MAD）治疗阻塞性睡眠呼吸暂停（OSA）的反应预测模型。
本研究在标识符NCT05596825下注册，根据标准化方案，前瞻性地分析了使用两件式可调节矫治器进行的6年MAD治疗。建立了与最新OSA严重程度国际共识声明一致的两种反应定义。逻辑回归和CHAID模型整合了基线临床、人体测量、头影测量解剖、软组织特征和生理上气道变量。
共有112名患者完成了研究：根据反应定义1，64名反应者和48名无反应者；根据反应定义2，81名反应者和31名无反应者。MAD治疗的反应者体重指数（BMI）、颈围和腰围、爱泼华嗜睡量表评分、呼吸暂停低通气指数（AHI）、视觉模拟量表上的打鼾强度、持续气道正压通气（CPAP）压力较低，而T90%和最低血氧饱和度（minSaO）较高。表现出更大解剖失衡、更小气道容积、更小最小横截面积（CSAmin）和更长气道长度的患者对治疗反应较差。
气道长度、初始T90%和前面部高度共同构成了反应定义1的高度预测性逻辑回归模型。贾拉巴克比率、下颌角、CSAmin、气道长度、初始BMI和基线AHI构成了第二个反应定义的高度预测模型。此外，CHAID回归树为构成预测模型的变量建立了截断值。
