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基于音频的数字生物标志物用于诊断和管理呼吸系统疾病:系统性审查和文献计量分析
Vivianne Landry1,2, Jessica Matschek2,3, Roger Pang2,3
1Faculty of Medicine, University of Montreal, Montreal, QC, Canada.
概括
数字音频生物标志物在诊断呼吸系统疾病 (如喘和COPD) 时具有中等到高的准确性. 需要进一步的研究来验证这些工具在不同的人群中用于更广泛的临床应用.
科学领域:
- 呼吸系统医学 呼吸系统医学
- 生物医学工程 生物医学工程
- 数据科学数据科学数据科学
背景情况:
- 数字音频生物标志物利用可穿戴传感器和人工智能进行疾病诊断.
- 呼吸护理中的音频生物标志物的临床证据目前是分散的.
- 现有的研究缺乏对其诊断准确性和应用的全面分析.
研究的目的:
- 在呼吸系统医学中对数字音频生物标志物进行文献计量分析和系统审查.
- 评估当前的研究环境,诊断准确性和音频生物标志物的临床实用性.
- 确定数字呼吸道诊断领域的基本和新兴主题.
主要方法:
- 在MEDLINE,Embase,Cochrane图书馆和CINAHL进行系统的文献搜索,直到2024年4月.
- 包括评估声音分析用于诊断阻塞性 (喘,COPD) 和传染性呼吸道疾病 (不包括COVID-19) 的研究.
- 使用QUADAS-2工具进行文献计量分析,叙事综合和质量评估.
主要成果:
- 从最初确定的14,180项研究中,包括了81项研究.
- 音频生物标志物表现出中等到高的诊断准确度 (60-100%).
- 对于喘 (80%),COPD (78%的敏感性,56%的特异性) 和肺炎 (64%的敏感性或特异性) 报告了高度的敏感性和特异性.
结论:
- 数字音频生物标志物在诊断和监测呼吸道疾病方面显示出显著的前景.
- 进一步的研究应该解决方法异质性和算法偏差.
- 成功实施可以加强远程医疗,传染病监测和慢性疾病管理.
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