Community Use of Digital Auscultation to Improve Diagnosis of Pediatric Pneumonia in Sylhet, Bangladesh

Detailed Summary

This study aims to evaluate an automated interpretation algorithm of recorded lung sound by a digital stethoscope, name the Smartscope, among rural Bangladeshi children receiving community care in order to improve the diagnosis of childhood pneumonia at first level facility in low- and middle-income countries. A mixed-methods study will be conducted for a period of twelve months in rural Sylhet, Bangladesh. A total of 12 community health workers (CHWs) and 12 community healthcare providers (CHCPs) will be recruited and trained for this study. CHWs will conduct household surveillance to identify children with cough and difficult breathing and refer to nearby community clinic (CC). The CHCPs will screen the children at the CCs as per protocol and enroll the suspected cases with couth or difficult breathing. A total of 1003 children will be enrolled in this study. Enrolled children will be assessed for signs and symptoms of pneumonia including oxygen saturation. The children will have their lung sounds recorded by the Smartscope at four sequential locations. A listening panel comprises by pediatricians will generate one summary patient classification of normal, crackle, wheeze, crackle and wheeze, or uninterpretable. The Respiratory detector automated algorithm will be applied to the lung recording to generate an interpretation. The study hypothesis is more than 50% of patients will have quality lung sound recordings and the agreement between the automated computerized analysis by Respiratory Detector and an expert listening panel will be high (kappa \>0.5).

Study Details

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Interventions