Observational studyBMJ open2022
Digital auscultation as a novel childhood pneumonia diagnostic tool for community clinics in Sylhet, Bangladesh: protocol for a cross-sectional study.
Observational study in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Community Use of Digital Auscultation to Improve Diagnosis of Pediatric Pneumonia in Sylhet, Bangladesh
The LalelaLung Study: Digital Stethoscope Clinical Evaluation
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Mapping national information and communication technology (ICT) infrastructure to the requirements of potential digital health interventions in low- and middle-income countries.Journal of global health · 2022Pooled it
- Operationalising the ESSENCE principles for equitable global health research partnerships in low- and middle-income countries: lessons from the RESPIRE collaboration.Journal of global health · 2026Article
- Digital stethoscope use by non-physician primary care health workers on children under five years of age in rural Bangladesh: a feasibility study.Scientific reports · 2026Article
- Evaluating the performance of community health care providers in detecting fast breathing in children using a reference video expert panel in Bangladesh.Discover public health · 2026Article
- Evaluating the performance of a video expert panel in assessing respiratory rate from recorded videos for the diagnosis of non-severe paediatric pneumonia.BMJ open respiratory research · 2025Article
- Health systems appraisal of the response to antimicrobial resistance in low- and middle-income countries in relation to COVID-19: Application of the WHO building blocks.Global policy · 2023Article
- The Role of Telemedicine in the Treatment of Cognitive and Psychological Disorders in Parkinson's Disease: An Overview.Brain sciences · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 7 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.