Obstructive sleep apnoea (OSA) is characterised by pharyngeal obstruction occurring at different sites. Endoscopic studies reveal that epiglottic collapse renders patients at higher risk of failed oral appliance therapy or accentuated collapse on continuous positive airway pressure. Diagnosing epiglottic collapse currently requires invasive studies (imaging and endoscopy). As an alternative, we propose that epiglottic collapse can be detected from the distinct airflow patterns it produces during sleep. 23 OSA patients underwent natural sleep endoscopy. 1232 breaths were scored as epiglottic/nonepiglottic collapse. Several flow characteristics were determined from the flow signal (recorded simultaneously with endoscopy) and used to build a predictive model to distinguish epiglottic from nonepiglottic collapse. Additionally, 10 OSA patients were studied to validate the pneumotachograph flow features using nasal pressure signals. Epiglottic collapse was characterised by a rapid fall(s) in the inspiratory flow, more variable inspiratory and expiratory flow and reduced tidal volume. The cross-validated accuracy was 84%. Predictive features obtained from pneumotachograph flow and nasal pressure were strongly correlated. This study demonstrates that epiglottic collapse can be identified from the airflow signal measured during a sleep study. This method may enable clinicians to use clinically collected data to characterise underlying physiology and improve treatment decisions. Epiglottic collapse can be identified from airflow characteristics during sleep http://ow.ly/IafB30dbD60

中文翻译：

---

预测阻塞性睡眠呼吸暂停患者的会厌塌陷

阻塞性睡眠呼吸暂停 (OSA) 的特征是咽部阻塞发生在不同部位。内窥镜研究表明，会厌塌陷使患者面临更高的口腔矫治器治疗失败风险或在持续气道正压通气时加重塌陷。诊断会厌塌陷目前需要侵入性研究（成像和内窥镜检查）。作为替代方案，我们建议会厌塌陷可以从它在睡眠期间产生的不同气流模式中检测到。23 名 OSA 患者接受了自然睡眠内窥镜检查。1232 次呼吸被计为会厌/非会厌塌陷。从流量信号（与内窥镜检查同时记录）确定几个流量特征，并用于构建预测模型以区分会厌塌陷和非会厌塌陷。此外，研究了 10 名 OSA 患者，以使用鼻压信号验证呼吸速度描记器流量特征。会厌塌陷的特征是吸气流量快速下降，吸气和呼气流量变化更大，潮气量减少。交叉验证的准确率为 84%。从呼吸速度描记器流量和鼻压获得的预测特征密切相关。这项研究表明，会厌塌陷可以从睡眠研究期间测量的气流信号中识别出来。这种方法可以使临床医生能够使用临床收集的数据来表征潜在的生理学并改进治疗决策。会厌塌陷可以通过睡眠期间的气流特征来识别 http://ow.ly/IafB30dbD60 会厌塌陷的特征是吸气流量快速下降，吸气和呼气流量变化更大，潮气量减少。交叉验证的准确率为 84%。从呼吸速度描记器流量和鼻压获得的预测特征密切相关。这项研究表明，会厌塌陷可以从睡眠研究期间测量的气流信号中识别出来。这种方法可以使临床医生能够使用临床收集的数据来表征潜在的生理学并改进治疗决策。会厌塌陷可以通过睡眠期间的气流特征来识别 http://ow.ly/IafB30dbD60 会厌塌陷的特征是吸气流量快速下降，吸气和呼气流量变化更大，潮气量减少。交叉验证的准确率为 84%。从呼吸速度描记器流量和鼻压获得的预测特征密切相关。这项研究表明，会厌塌陷可以从睡眠研究期间测量的气流信号中识别出来。这种方法可以使临床医生能够使用临床收集的数据来表征潜在的生理学并改进治疗决策。会厌塌陷可以通过睡眠期间的气流特征来识别 http://ow.ly/IafB30dbD60 从呼吸速度描记器流量和鼻压获得的预测特征密切相关。这项研究表明，会厌塌陷可以从睡眠研究期间测量的气流信号中识别出来。这种方法可以使临床医生能够使用临床收集的数据来表征潜在的生理学并改进治疗决策。会厌塌陷可以通过睡眠期间的气流特征来识别 http://ow.ly/IafB30dbD60 从呼吸速度描记器流量和鼻压获得的预测特征密切相关。这项研究表明，会厌塌陷可以从睡眠研究期间测量的气流信号中识别出来。这种方法可以使临床医生能够使用临床收集的数据来表征潜在的生理学并改进治疗决策。会厌塌陷可以通过睡眠期间的气流特征来识别 http://ow.ly/IafB30dbD60