哮喘联盟

    计算机化的肺部听诊分析是通过特有的波谱分析模式鉴定哮鸣音的一种敏感而定量的方法。该项研究评估了一种具有多个传感器、以计算机为基础的可自动化检测哮鸣音的VRI设备的检测准确性。该方法通过对比听诊7例哮喘或慢性阻塞性肺疾病和7名正常人的肺部，检查音频文件和电脑检测哮鸣音对100个声音文件进行验证。三位盲法医生确定了40个有哮鸣音的声音文件和60个无哮鸣音的声音文件。敏感性和特异性分别为83％和85％。阴性预测值和阳性预测值分别为89％和79％。总的预测符合率为84％。假阳性病例可闻及似哮鸣音的声音，如不用听诊器也可听到的背景噪音、喉咙发出的高频率强烈噪声。
   本研究结果表明，使用单一传感器和多个传感器进行区域哮鸣音检测具有良好的准确性，敏感性，特异性，阴性预测值和阳性预测值，结果与文献报道类似。该设备易于使用，无需患者过多努力，有别于其他设备的特点是：它可以在不到1分钟内就可提供一个带哮鸣音检测输出的呼吸音分布动态图像。

（林江涛 审校）
Guntupalli KK, et al. J Asthma. 2008 Dec;45(10):903-907.

Validation of automatic wheeze detection in patients with obstructed airways and in healthy subjects.

Guntupalli KK, Alapat PM, Bandi VD, Kushnir I.
Baylor College of Medicine, Houston, TX.

Computerized lung-sound analysis is a sensitive and quantitative method to identify wheezing by its typical pattern on spectral analysis. We evaluated the accuracy of the VRI, a multi-sensor, computer-based device with an automated technique of wheeze detection. The method was validated in 100 sound files from seven subjects with asthma or chronic obstructive pulmonary disease and seven healthy subjects by comparison of auscultation findings, examination of audio files, and computer detection of wheezes. Three blinded physicians identified 40 sound files with wheezes and 60 sound files without wheezes. Sensitivity and specificity were 83% and 85%, respectively. Negative predictive value and positive predictive value were 89% and 79%, respectively. Overall inter-rater agreement was 84%. False positive cases were found to contain sounds that simulate wheezes, such as background noises with high frequencies or strong noises from the throat that could be heard and identified without a stethoscope. The present findings demonstrate that the wheeze detection algorithm has good accuracy, sensitivity, specificity, negative predictive value and positive predictive value for wheeze detection in regional analyses with a single sensor and multiple sensors. Results are similar to those reported in the literature. The device is user-friendly, requires minimal patient effort, and, distinct from other devices, it provides a dynamic image of breath sound distribution with wheeze detection output in less than 1 minute.