PT - JOURNAL ARTICLE AU - Raymond LH Murphy AU - Andrey Vyshedskiy AU - Verna-Ann Power-Charnitsky AU - Dhirendra S Bana AU - Patricia M Marinelli AU - Anna Wong-Tse AU - Rozanne Paciej TI - Automated Lung Sound Analysis in Patients With Pneumonia DP - 2004 Dec 01 TA - Respiratory Care PG - 1490--1497 VI - 49 IP - 12 4099 - http://rc.rcjournal.com/content/49/12/1490.short 4100 - http://rc.rcjournal.com/content/49/12/1490.full AB - BACKGROUND: To determine whether objectively detected lung sounds were significantly different in patients with pneumonia than those in asymptomatic subjects, and to quantify the pneumonia findings for teaching purposes. METHODS: At a community teaching hospital we used a multi-channel lung sound analyzer to examine a learning sample of 50 patients diagnosed with pneumonia and 50 control subjects. Automated quantification and characterization of the lung sounds commonly recognized to be associated with pneumonia were used to generate an “acoustic pneumonia score.“ These were examined in the learning sample and then prospectively tested in 50 patients and 50 controls. RESULTS: The acoustic pneumonia score averaged 13 in the learning sample and 11 in the test sample of pneumonia patients. The scores were 2 and 3 in the controls. The positive predictive value of a score higher than 6 was 0.94 in the learning sample and 0.87 in the test sample. The sensitivities in the 2 groups were 0.90 and 0.78, and the specificities were 0.94 and 0.88, respectively. Adventitious sounds were more common in pneumonia patients (inspiratory crackles 81% vs 28%, expiratory crackles 65% vs 9%, rhonchi 19% vs 0%). CONCLUSIONS: Our lung sound analyzer found significant differences between lung sounds in patients with pneumonia and in asymptomatic controls. Computerized lung sound analysis can provide objective evidence supporting the diagnosis of pneumonia. We believe that the lung-sound data produced by our device will help to teach physical diagnosis.