a Pneumology Service , Río Hortega University Hospital , Valladolid , Spain.
b Biomedical Engineering Group , University of Valladolid , Valladolid , Spain.
Expert Rev Respir Med. 2018 Aug;12(8):665-681. doi: 10.1080/17476348.2018.1495563. Epub 2018 Jul 26.
Overnight oximetry has been proposed as an accessible, simple, and reliable technique for obstructive sleep apnea syndrome (OSAS) diagnosis. From visual inspection to advanced signal processing, several studies have demonstrated the usefulness of oximetry as a screening tool. However, there is still controversy regarding the general application of oximetry as a single screening methodology for OSAS. Areas covered: Currently, high-resolution portable devices combined with pattern recognition-based applications are able to achieve high performance in the detection of this disease. In this review, recent studies involving automated analysis of oximetry by means of advanced signal processing and machine learning algorithms are analyzed. Advantages and limitations are highlighted and novel research lines aimed at improving the screening ability of oximetry are proposed. Expert commentary: Oximetry is a cost-effective tool for OSAS screening in patients showing high pretest probability for the disease. Nevertheless, exhaustive analyses are still needed to further assess unattended oximetry monitoring as a single diagnostic test for sleep apnea, particularly in the pediatric population and in populations with significant comorbidities. In the following years, communication technologies and big data analyses will overcome current limitations of simplified sleep testing approaches, changing the detection and management of OSAS.
整夜血氧饱和度监测已被提出作为阻塞性睡眠呼吸暂停综合征（OSAS）诊断的一种易于获取、简单且可靠的技术。从目视检查到先进的信号处理，多项研究已经证明了血氧饱和度监测作为一种筛查工具的有用性。然而，关于将血氧饱和度监测作为 OSAS 的单一筛查方法的普遍应用仍存在争议。
目前，高分辨率便携式设备与基于模式识别的应用相结合，能够在检测这种疾病方面取得高性能。在这篇综述中，分析了涉及先进信号处理和机器学习算法的自动血氧饱和度分析的最新研究。强调了其优点和局限性，并提出了旨在提高血氧饱和度筛查能力的新研究方向。
对于表现出该疾病高术前概率的患者，血氧饱和度监测是 OSAS 筛查的一种具有成本效益的工具。然而，仍需要进行详尽的分析，以进一步评估无监护血氧饱和度监测作为睡眠呼吸暂停的单一诊断测试，特别是在儿科人群和存在重大合并症的人群中。在未来几年，通信技术和大数据分析将克服简化睡眠测试方法的当前局限性，改变 OSAS 的检测和管理。
