Evidence map›Paper›PMID 35140164›Full record

Observational studyBMJ open2022

Digital auscultation as a novel childhood pneumonia diagnostic tool for community clinics in Sylhet, Bangladesh: protocol for a cross-sectional study.

Salahuddin Ahmed, Dipak Kumar Mitra, Harish Nair, Steven Cunningham, Ahad Mahmud Khan, Asmd Ashraful Islam, Ian Mitra McLane, Nabidul Haque Chowdhury, Nazma Begum, Mohammod Shahidullah and 6 more

2 registry-linked trialsOpen access · goldAbstract readObservational Study
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT03959956 completednot on this map

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

TypeobservationalSponsorUniversity of EdinburghRan2019 to 2023Enrolled990ConditionsChildhood PneumoniaArmsRecording lung sound by a Smartscope
NCT07631377 phase4not yet recruitingnot on this mapstarted 2026, after this paper: background citation

The LalelaLung Study: Digital Stethoscope Clinical Evaluation

TypeinterventionalSponsorJohns Hopkins UniversityRan2026 to 2028Enrolled350ConditionsPneumonia, Tuberculosis, Pulmonary, Respiratory Tract Infections, BronchiolitisArmsStethoMe AI-enabled digital stethoscope system, Standard IMCI assessment
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 7 institutions in 3 countries.

Salahuddin AhmedProjahnmo Research Foundation, Dhaka, Bangladesh sahmed773@yahoo.com.ORCID 0000-0001-6771-0638
Dipak Kumar MitraProjahnmo Research Foundation, Dhaka, Bangladesh.
Harish NairUsher Institute, The University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-9432-9100
Steven CunninghamDepartment of Child Life and Health, Royal Hospital for Sick Children, Edinburgh, UK.ORCID 0000-0001-7342-251X
Ahad Mahmud KhanProjahnmo Research Foundation, Dhaka, Bangladesh.ORCID 0000-0002-4347-0825
Asmd Ashraful IslamProjahnmo Research Foundation, Dhaka, Bangladesh.ORCID 0000-0003-1597-4847
Ian Mitra McLaneSonavi Labs, Baltimore, Maryland, USA.
Nabidul Haque ChowdhuryProjahnmo Research Foundation, Dhaka, Bangladesh.
Nazma BegumProjahnmo Research Foundation, Dhaka, Bangladesh.
Mohammod ShahidullahDepartment of Neonatology, Bangabandhu Sheikh Mujib Medical University, Dhaka, Bangladesh.
Muhammad Shariful IslamDirectorate General of Health Services, Ministry of Health and Family Welfare, Government of Bangladesh, Dhaka, Bangladesh.
John NorrieUsher Institute, Edinburgh Clinical Trials Unit, University of Edinburgh No. 9, Bioquarter, Edinburgh, UK.ORCID 0000-0001-9823-9252
Harry CampbellUsher Institute, The University of Edinburgh, Edinburgh, UK.
Aziz SheikhUsher Institute, The University of Edinburgh, Edinburgh, UK.
Abdullah H BaquiDepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
Eric D McCollumDepartment of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0002-1872-5566
Biomedical Research Foundation · BDUniversity of Edinburgh · GBJohns Hopkins University · USBangladesh Medical University · BDDirectorate General of Health Services · BDNorth South University · BDRoyal Hospital for Children · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

PneumoniaRespiratory SoundsAuscultationBangladeshChild, PreschoolClinical ProtocolsCross-Sectional StudiesHumansInfantReproducibility of Resultscommunity child healthpaediatric infectious disease & immunisationrespiratory infections

Identifiers

PMID35140164
PMCPMC8830242
OpenAlexW4210856313

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.