TY - JOUR
T1 - Digital auscultation as a novel childhood pneumonia diagnostic tool for community clinics in Sylhet, Bangladesh
T2 - protocol for a cross-sectional study
AU - Ahmed, Salahuddin
AU - Mitra, Dipak
AU - Nair, Harish
AU - Cunningham, Steve
AU - Khan, Ahad
AU - Islam, Ashraful
AU - McLane, Ian
AU - Chowdhury, Nabidul
AU - Begum, Nazma
AU - Shahidullah, Mohammod
AU - Islam, Muhammad Shariful
AU - Norrie, John
AU - Campbell, Harry
AU - Sheikh, Aziz
AU - Baqui, Abdullah H.
AU - McCollum, Eric D
N1 - Funding Information:
Funding This research was funded by the UK National Institute for Health Research (NIHR) (Global Health Research Unit on Respiratory Health (RESPIRE); Grant number 16/136/109) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Government. The RESPIRE collaboration comprises the UK Grant holders, Partners and research teams as listed on the RESPIRE website (https://www.ed.ac.uk/usher/respire) including Sian Williams.
Publisher Copyright:
© 2022 Author(s). Published by BMJ.
PY - 2022/2/9
Y1 - 2022/2/9
N2 - INTRODUCTION: The WHO's Integrated Management of Childhood Illnesses (IMCI) algorithm for diagnosis of child pneumonia relies on counting respiratory rate and observing respiratory distress to diagnose childhood pneumonia. IMCI case defination for pneumonia performs with high sensitivity but low specificity, leading to overdiagnosis of child pneumonia and unnecessary antibiotic use. Including lung auscultation in IMCI could improve specificity of pneumonia diagnosis. Our objectives are: (1) assess lung sound recording quality by primary healthcare workers (HCWs) from under-5 children with the Feelix Smart Stethoscope and (2) determine the reliability and performance of recorded lung sound interpretations by an automated algorithm compared with reference paediatrician interpretations.METHODS AND ANALYSIS: In a cross-sectional design, community HCWs will record lung sounds of ~1000 under-5-year-old children with suspected pneumonia at first-level facilities in Zakiganj subdistrict, Sylhet, Bangladesh. Enrolled children will be evaluated for pneumonia, including oxygen saturation, and have their lung sounds recorded by the Feelix Smart stethoscope at four sequential chest locations: two back and two front positions. A novel sound-filtering algorithm will be applied to recordings to address ambient noise and optimise recording quality. Recorded sounds will be assessed against a predefined quality threshold. A trained paediatric listening panel will classify recordings into one of the following categories: normal, crackles, wheeze, crackles and wheeze or uninterpretable. All sound files will be classified into the same categories by the automated algorithm and compared with panel classifications. Sensitivity, specificity and predictive values, of the automated algorithm will be assessed considering the panel's final interpretation as gold standard.ETHICS AND DISSEMINATION: The study protocol was approved by the National Research Ethics Committee of Bangladesh Medical Research Council, Bangladesh (registration number: 09630012018) and Academic and Clinical Central Office for Research and Development Medical Research Ethics Committee, Edinburgh, UK (REC Reference: 18-HV-051). Dissemination will be through conference presentations, peer-reviewed journals and stakeholder engagement meetings in Bangladesh.TRIAL REGISTRATION NUMBER: NCT03959956.
AB - INTRODUCTION: The WHO's Integrated Management of Childhood Illnesses (IMCI) algorithm for diagnosis of child pneumonia relies on counting respiratory rate and observing respiratory distress to diagnose childhood pneumonia. IMCI case defination for pneumonia performs with high sensitivity but low specificity, leading to overdiagnosis of child pneumonia and unnecessary antibiotic use. Including lung auscultation in IMCI could improve specificity of pneumonia diagnosis. Our objectives are: (1) assess lung sound recording quality by primary healthcare workers (HCWs) from under-5 children with the Feelix Smart Stethoscope and (2) determine the reliability and performance of recorded lung sound interpretations by an automated algorithm compared with reference paediatrician interpretations.METHODS AND ANALYSIS: In a cross-sectional design, community HCWs will record lung sounds of ~1000 under-5-year-old children with suspected pneumonia at first-level facilities in Zakiganj subdistrict, Sylhet, Bangladesh. Enrolled children will be evaluated for pneumonia, including oxygen saturation, and have their lung sounds recorded by the Feelix Smart stethoscope at four sequential chest locations: two back and two front positions. A novel sound-filtering algorithm will be applied to recordings to address ambient noise and optimise recording quality. Recorded sounds will be assessed against a predefined quality threshold. A trained paediatric listening panel will classify recordings into one of the following categories: normal, crackles, wheeze, crackles and wheeze or uninterpretable. All sound files will be classified into the same categories by the automated algorithm and compared with panel classifications. Sensitivity, specificity and predictive values, of the automated algorithm will be assessed considering the panel's final interpretation as gold standard.ETHICS AND DISSEMINATION: The study protocol was approved by the National Research Ethics Committee of Bangladesh Medical Research Council, Bangladesh (registration number: 09630012018) and Academic and Clinical Central Office for Research and Development Medical Research Ethics Committee, Edinburgh, UK (REC Reference: 18-HV-051). Dissemination will be through conference presentations, peer-reviewed journals and stakeholder engagement meetings in Bangladesh.TRIAL REGISTRATION NUMBER: NCT03959956.
KW - Auscultation
KW - Bangladesh
KW - Child, Preschool
KW - Clinical Protocols
KW - Cross-Sectional Studies
KW - Humans
KW - Infant
KW - Pneumonia/diagnosis
KW - Reproducibility of Results
KW - Respiratory Sounds/diagnosis
U2 - 10.1136/bmjopen-2021-059630
DO - 10.1136/bmjopen-2021-059630
M3 - Article
C2 - 35140164
SN - 2044-6055
VL - 12
SP - e059630
JO - BMJ Open
JF - BMJ Open
IS - 2
ER -