Visscher Wouter P, Ho Jean-Pierre T F, Zhou Ning, Ravesloot Madeline J L, Schulten Engelbert A J M, Lange Jan de, Su Naichuan
Amsterdam UMC and Academic Centre for Dentistry Amsterdam (ACTA), Department of Oral and Maxillofacial Surgery/Oral Pathology, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands.
Department of Oral and Maxillofacial Surgery, Noordwest Ziekenhuisgroep, 1815 JD Alkmaar, The Netherlands.
J Clin Med. 2023 Jan 7;12(2):503. doi: 10.3390/jcm12020503.
Background: Maxillomandibular advancement (MMA) has been shown to be the most effective surgical therapy for obstructive sleep apnea (OSA). Despite high success rates, there are patients who are considered as non-responders to MMA. In order to triage and inform these patients on their expected prognosis of MMA before the surgery, this study aimed to develop, internally validate, and calibrate a prediction model for the presence of surgical success for MMA in patients with OSA. Methods: A retrospective cohort study was conducted that included patients that had undergone MMA for moderate to severe OSA. Baseline clinical, polysomnographic, cephalometric, and drug-induced sleep endoscopy findings were recorded as potential predictors. Presence or absence of surgical success was recorded as outcome. Binary logistic regression analyses were conducted to develop the model. Performance and clinical values of the model were analyzed. Results: One hundred patients were included, of which sixty-seven (67%) patients reached surgical success. Anterior lower face height (ALFH) (OR: 0.93 [0.87−1.00], p = 0.05), superior posterior airway space (SPAS) (OR: 0.76 [0.62−0.92], p < 0.05), age (OR: 0.96 [0.91−1.01], p = 0.13), and a central apnea index (CAI) <5 events/hour sleep (OR: 0.16 [0.03−0.91], p < 0.05) were significant independent predictors in the model (significance level set at p = 0.20). The model showed acceptable discrimination with a shrunken area under the curve of 0.74, and acceptable calibration. The added predictive values for ruling in and out of surgical success were 0.21 and 0.32, respectively. Conclusions: Lower age at surgery, CAI < 5 events/hour, lower ALFH, and smaller SPAS were significant predictors for the surgical success of MMA. The discrimination, calibration, and clinical added values of the model were acceptable.
上颌下颌前移术(MMA)已被证明是治疗阻塞性睡眠呼吸暂停(OSA)最有效的手术疗法。尽管成功率很高,但仍有一些患者被认为是MMA治疗无反应者。为了在手术前对这些患者进行分类并告知他们MMA的预期预后,本研究旨在开发、内部验证并校准一个预测阻塞性睡眠呼吸暂停患者MMA手术成功与否的模型。方法:进行了一项回顾性队列研究,纳入了接受MMA治疗中度至重度OSA的患者。记录基线临床、多导睡眠图、头影测量和药物诱导睡眠内镜检查结果作为潜在预测因素。记录手术成功与否作为结果。进行二元逻辑回归分析以建立模型。分析模型的性能和临床价值。结果:纳入100例患者,其中67例(67%)患者手术成功。下颌前部面高(ALFH)(比值比:0.93[0.87 - 1.00],p = 0.05)、上后气道间隙(SPAS)(比值比:0.76[0.62 - 0.92],p < 0.05)、年龄(比值比:0.96[0.91 - 1.01],p = 0.13)和中枢性呼吸暂停指数(CAI)<5次/小时睡眠(比值比:0.16[0.03 - 0.91],p < 0.05)是模型中的显著独立预测因素(显著性水平设定为p = 0.20)。该模型显示出可接受的区分度,曲线下面积缩小后为0.74,校准也可接受。判断手术成功的附加预测值和排除手术成功的附加预测值分别为0.21和0.32。结论:手术时年龄较小、CAI<5次/小时、ALFH较低和SPAS较小是MMA手术成功的显著预测因素。该模型的区分度、校准度和临床附加值均可接受。