Pneumology Department, Río Hortega University Hospital, Valladolid, Spain.
Biomedical Engineering Group (GIB), University of Valladolid, Valladolid, Spain.
Adv Exp Med Biol. 2022;1384:43-61. doi: 10.1007/978-3-031-06413-5_4.
Obstructive sleep apnea (OSA) is a heterogeneous disease with many physiological implications. OSA is associated with a great diversity of diseases, with which it shares common and very often bidirectional pathophysiological mechanisms, leading to significantly negative implications on morbidity and mortality. In these patients, underdiagnosis of OSA is high. Concerning cardiorespiratory comorbidities, several studies have assessed the usefulness of simplified screening tests for OSA in patients with hypertension, COPD, heart failure, atrial fibrillation, stroke, morbid obesity, and in hospitalized elders.The key question is whether there is any benefit in the screening for the existence of OSA in patients with comorbidities. In this regard, there are few studies evaluating the performance of the various diagnostic procedures in patients at high risk for OSA. The purpose of this chapter is to review the existing literature about diagnosis in those diseases with a high risk for OSA, with special reference to artificial intelligence-related methods.
阻塞性睡眠呼吸暂停(OSA)是一种具有多种生理影响的异质性疾病。OSA 与许多疾病相关,这些疾病具有共同的且非常常见的双向病理生理机制,导致发病率和死亡率显著下降。在这些患者中,OSA 的漏诊率很高。关于心肺合并症,多项研究评估了简化的 OSA 筛查试验在高血压、COPD、心力衰竭、心房颤动、中风、病态肥胖和住院老年人患者中的作用。关键问题是在合并症患者中筛查 OSA 是否有任何益处。在这方面,评估各种诊断程序在 OSA 高危患者中的表现的研究很少。本章的目的是回顾有关具有 OSA 高风险的这些疾病的诊断的现有文献,特别参考与人工智能相关的方法。