Evidence map›Paper›PMID 35493777›Full record

SynthesisJournal of global health2022

Digital auscultation as a diagnostic aid to detect childhood pneumonia: A systematic review.

Salahuddin Ahmed, Saima Sultana, Ahad M Khan, Mohammad S Islam, Gm Monsur Habib, Ian M McLane, Eric D McCollum, Abdullah H Baqui, Steven Cunningham, Harish Nair

Registry-linked trialOpen access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Journal of global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07362433 (The BLAAAST Trial), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 21% 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.

NCT07362433 phase4recruitingnot on this mapstarted 2026, after this paper: background citation

The BLAAAST Trial: Bangladesh Lung Auscultation AI for Antibiotic Stewardship Randomized Controlled Trial

TypeinterventionalSponsorJohns Hopkins UniversityRan2026 to 2029Enrolled2,500ConditionsRespiratory Infections in ChildrenArmsAutomated digital stethoscope
3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
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

10 authors at 4 institutions in 3 countries.

Salahuddin AhmedUsher Institute, University of Edinburgh, Edinburgh, UK.
Saima SultanaProjahnmo Research Foundation, Dhaka, Bangladesh.
Ahad M KhanUsher Institute, University of Edinburgh, Edinburgh, UK.
Mohammad S IslamUsher Institute, University of Edinburgh, Edinburgh, UK.
Gm Monsur HabibUsher Institute, University of Edinburgh, Edinburgh, UK.
Ian M McLaneSonavi Labs, Baltimore, Maryland, USA.
Eric D McCollumGlobal Program for Pediatric Respiratory Sciences, Eudowood Division of Paediatric Respiratory Sciences, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Abdullah H BaquiDepartment of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
Steven CunninghamDepartment of Child Life and Health, Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK.
Harish NairUsher Institute, University of Edinburgh, Edinburgh, UK.
Biomedical Research Foundation · BDUniversity of Edinburgh · GBJohns Hopkins University · USCentre for Inflammation Research · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Frontline health care workers use World Health Organization Integrated Management of Childhood Illnesses (IMCI) guidelines for child pneumonia care in low-resource settings. IMCI guideline pneumonia diagnostic criterion performs with low specificity, resulting in antibiotic overtreatment. Digital auscultation with automated lung sound analysis may improve the diagnostic performance of IMCI pneumonia guidelines. This systematic review aims to summarize the evidence on detecting adventitious lung sounds by digital auscultation with automated analysis compared to reference physician acoustic analysis for child pneumonia diagnosis. Methods: In this review, articles were searched from MEDLINE, Embase, CINAHL Plus, Web of Science, Global Health, IEEExplore database, Scopus, and the ClinicalTrial.gov databases from the inception of each database to October 27, 2021, and reference lists of selected studies and relevant review articles were searched manually. Studies reporting diagnostic performance of digital auscultation and/or computerized lung sound analysis compared against physicians' acoustic analysis for pneumonia diagnosis in children under the age of 5 were eligible for this systematic review. Retrieved citations were screened and eligible studies were included for extraction. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. All these steps were independently performed by two authors and disagreements between the reviewers were resolved through discussion with an arbiter. Narrative data synthesis was performed. Results: A total of 3801 citations were screened and 46 full-text articles were assessed. 10 studies met the inclusion criteria. Half of the studies used a publicly available respiratory sound database to evaluate their proposed work. Reported methodologies/approaches and performance metrics for classifying adventitious lung sounds varied widely across the included studies. All included studies except one reported overall diagnostic performance of the digital auscultation/computerised sound analysis to distinguish adventitious lung sounds, irrespective of the disease condition or age of the participants. The reported accuracies for classifying adventitious lung sounds in the included studies varied from 66.3% to 100%. However, it remained unclear to what extent these results would be applicable for classifying adventitious lung sounds in children with pneumonia. Conclusions: This systematic review found very limited evidence on the diagnostic performance of digital auscultation to diagnose pneumonia in children. Well-designed studies and robust reporting are required to evaluate the accuracy of digital auscultation in the paediatric population.

Indexed as

PneumoniaRespiratory SoundsAuscultationChildHumansLung

Identifiers

PMID35493777
PMCPMC9024283
OpenAlexW4224223768

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.