Improving Community-Based Diagnosis of Acute Lower Respiratory Illness
The primary aim of this project is to determine the specificity and sensitivity of a new digital chest auscultation device to diagnose pneumonia and quantify the improvement upon the current WHO algorithm. When used by trained community-based health workers this algorithm has high sensitivity but low specificity for the diagnosis of pneumonia (1). The issue of low specificity and the misclassification of children can have significant consequences in both the management of pneumonia as well as outcome and effect size measurements in pneumonia prevention and intervention research trials. The use of chest auscultation using a stethoscope to diagnose pneumonia was the first diagnostic instrument to be widely used by clinicians. However, subjectivity in the interpretation of chest sounds, limitations of the human ear, and dependence on the skill level of medical personnel has limited its use in favor of more advanced diagnostic tests such as chest x-rays, or other imaging techniques. In low-resource settings, these advanced tests are not an option and diagnosis is reliant on clinical signs alone using the WHO algorithm. Analysis of auscultation recordings from a digital stethoscope allows for objectivity, decreased reliance on the memory and skill of the clinician and limiting exposure to radiation from chest x-rays. Digital stethoscopes can record chest sounds, reduce background noise, and amplify sounds that are typically outside the frequency range of an acoustic stethoscope. The ability to incorporate objective auscultation using a digital stethoscope into the WHO algorithm would increase the validity of this diagnostic tool in a low-resource setting.