Determination of the site of pharyngeal collapse in Obstructive Sleep Apnea patients from snoring sounds

摘要 阻塞性睡眠呼吸暂停(OSA)是一种普遍存在的疾病，由于治疗不佳而一直得不到治疗 坚持持续气道正压(CPAP)。多项研究表明，咽部 阻塞性睡眠呼吸暂停综合征患者不同部位(口膜、口咽侧壁、舌根、 和/或会厌)。此外，许多非CPAP治疗阻塞性睡眠呼吸暂停综合征的方法已被证明对 一些坍塌的地点比其他的要好。问题是，坍塌的地点需要昂贵的或侵入性的 程序，如药物诱导的睡眠内窥镜检查(DISE)。这项提案寻求通过以下方式解决这一问题 通过对鼾声的声学分析确定坍塌位置。 在目标1中，将利用DISE同时开发一个预测坍塌地点的模型 对800人的鼾声进行了测量。在目标2中，将在子集中执行自然睡眠内窥镜检查 以证实坍塌结构(S)在自然睡眠中发出的声音与 药物诱导的睡眠。最后，目标3将测试在家庭环境中测量鼾声的能力。 我们将比较来自自然睡眠内窥镜检查的鼾声和在家中自然睡眠的鼾声。 相同的个人)。此外，打呼噜将在不同的晚上在家里进行测量，以测试重复性 跨越黑夜。 这项资助中的研究有望产生一种估计咽部位置的算法 因鼾声而虚脱。该算法可以改进非CPAP治疗患者的选择 并有可能增加有效治疗阻塞性睡眠呼吸暂停综合征的患者数量。

ABSTRACT Obstructive Sleep Apnea (OSA) is a prevalent disorder that remains undertreated due to poor adherence with continuous positive airway pressure (CPAP). Several studies suggest that the pharyngeal airway can collapse at different sites in patients with OSA (velum, oropharyngeal lateral walls, tongue base, and/or epiglottis). Furthermore, many of the non-CPAP treatments for OSA have been shown to work better for some sites of collapse than others. The problem is, the site of collapse requires expensive or invasive procedures, such as drug-induced sleep endoscopy (DISE). This proposal seeks to solve that problem by determining the site of collapse from acoustic analysis of snoring sounds. In Aim 1, a model for predicting the site of collapse will be developed using DISE with simultaneously measured snoring sounds in 800 individuals. In Aim 2, natural sleep endoscopy will be performed in a subset of people from Aim 1 to confirm that the collapsing structure(s) produce the same sound in natural sleep as drug-induced sleep. Finally, Aim 3 will test the ability to measure snoring sounds in the home environment. Comparisons will be made between snores from natural sleep endoscopy and natural sleep at home (in the same individual). Additionally, snoring will be measured at home on separate nights to test reproducibility across nights. The studies in this grant are expected to produce an algorithm for estimating the site of pharyngeal collapse from snoring sounds. This algorithm could improve the selection of patients for non-CPAP therapies and potentially increase the number of patients effectively treated for OSA.