Zimmer Alexandra J, Ugarte-Gil César, Pathri Rahul, Dewan Puneet, Jaganath Devan, Cattamanchi Adithya, Pai Madhukar, Grandjean Lapierre Simon
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
McGill International TB Centre, Montreal, Canada.
Commun Med (Lond). 2022 Jul 6;2:83. doi: 10.1038/s43856-022-00149-w. eCollection 2022.
Cough assessment is central to the clinical management of respiratory diseases, including tuberculosis (TB), but strategies to objectively and unobtrusively measure cough are lacking. Acoustic epidemiology is an emerging field that uses technology to detect cough sounds and analyze cough patterns to improve health outcomes among people with respiratory conditions linked to cough. This field is increasingly exploring the potential of artificial intelligence (AI) for more advanced applications, such as analyzing cough sounds as a biomarker for disease screening. While much of the data are preliminary, objective cough assessment could potentially transform disease control programs, including TB, and support individual patient management. Here, we present an overview of recent advances in this field and describe how cough assessment, if validated, could support public health programs at various stages of the TB care cascade.
咳嗽评估是包括结核病（TB）在内的呼吸系统疾病临床管理的核心，但目前缺乏客观且不干扰患者的咳嗽测量策略。声学流行病学是一个新兴领域，它利用技术检测咳嗽声音并分析咳嗽模式，以改善与咳嗽相关的呼吸道疾病患者的健康状况。该领域越来越多地探索人工智能（AI）在更高级应用中的潜力，例如将咳嗽声音分析作为疾病筛查的生物标志物。虽然大部分数据尚属初步，但客观的咳嗽评估有可能改变包括结核病在内的疾病控制项目，并支持个体患者的管理。在此，我们概述该领域的最新进展，并描述咳嗽评估（如经验证）如何在结核病护理级联的各个阶段支持公共卫生项目。
