Department of Internal Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, University of Kentucky, Lexington, KY.
University of Manitoba, Department of Pediatrics and Child Health, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada.
Chest. 2023 Jun;163(6):1519-1528. doi: 10.1016/j.chest.2023.01.024. Epub 2023 Jan 25.
The association between breathing sounds and respiratory health or disease has been exceptionally useful in the practice of medicine since the advent of the stethoscope. Remote patient monitoring technology and artificial intelligence offer the potential to develop practical means of assessing respiratory function or dysfunction through continuous assessment of breathing sounds when patients are at home, at work, or even asleep. Automated reports such as cough counts or the percentage of the breathing cycles containing wheezes can be delivered to a practitioner via secure electronic means or returned to the clinical office at the first opportunity. This has not previously been possible. The four respiratory sounds that most lend themselves to this technology are wheezes, to detect breakthrough asthma at night and even occupational asthma when a patient is at work; snoring as an indicator of OSA or adequacy of CPAP settings; cough in which long-term recording can objectively assess treatment adequacy; and crackles, which, although subtle and often overlooked, can contain important clinical information when appearing in a home recording. In recent years, a flurry of publications in the engineering literature described construction, usage, and testing outcomes of such devices. Little of this has appeared in the medical literature. The potential value of this technology for pulmonary medicine is compelling. We expect that these tiny, smart devices soon will allow us to address clinical questions that occur away from the clinic.
自听诊器问世以来,呼吸音与呼吸健康或疾病之间的关联在医学实践中具有非常重要的作用。远程患者监测技术和人工智能有可能通过在患者在家、工作甚至睡眠时持续评估呼吸音,开发出实用的评估呼吸功能或功能障碍的方法。通过安全的电子手段,可向医生发送自动报告,如咳嗽次数或包含喘鸣的呼吸周期百分比,或者在第一时间将其返回临床办公室。这在以前是不可能的。最适合这项技术的四种呼吸音是喘鸣音,可用于夜间检测哮喘发作,甚至可在患者工作时检测职业性哮喘;鼾声作为 OSA 或 CPAP 设置是否充分的指标;咳嗽可通过长期记录客观评估治疗效果;而爆裂声虽然细微且经常被忽视,但在家庭录音中出现时可能包含重要的临床信息。近年来,工程文献中大量出版物描述了此类设备的构建、使用和测试结果。但在医学文献中很少出现。这项技术对肺病学的潜在价值是巨大的。我们期望这些小巧、智能的设备很快就能让我们解决远离诊所时出现的临床问题。