Evidence map›Paper›PMID 32355210›Full record

SynthesisScientific reports2020

The diagnostic accuracy of lung auscultation in adult patients with acute pulmonary pathologies: a meta-analysis.

Luca Arts, Endry Hartono Taslim Lim, Peter Marinus van de Ven, Leo Heunks, Pieter R Tuinman

2 registry-linked trialsOpen access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Scientific reports, 2020. 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 43 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 2 pooled it
7.6field-weighted citation impact, top 2% 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.

NCT05731180 naunknown statusnot on this mapstarted 2023, after this paper: background citation

The Efficacy of Medical Students to Correctly Recognise Pathological From Non-pathological Lung Sounds Over a Period of Time

TypeinterventionalSponsorLithuanian University of Health SciencesRan2023 to 2023Enrolled140ConditionsLung SoundArmsIdentify pathological and not pathological lung sounds
NCT05731193 nacompletednot on this mapstarted 2023, after this paper: background citation

The Effect of White Noise on the Ability of Second-year and Third-year Medical Students to Recognise Correctly Adventitious Lung Sound

TypeinterventionalSponsorLithuanian University of Health SciencesRan2023 to 2023Enrolled52ConditionsLung SoundArmsExposed group (EXP) - 35 students. EXP group will learn pathological and nonpathological sounds for 3 days.
3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 2 syntheses or guidelines pooled it, 104 citations in OpenAlex.

  1. Pooled it
  2. Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.European respiratory review : an official journal of the European Respiratory Society · 2025
    Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Observational
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

5 authors at 2 institutions in 1 country.

Luca ArtsAmsterdam UMC, location Vrije Universiteit Amsterdam, Department of Intensive Care Medicine, Amsterdam, The Netherlands.ORCID http://orcid.org/0000-0002-0627-0592
Endry Hartono Taslim LimAmsterdam UMC, location Vrije Universiteit Amsterdam, Department of Intensive Care Medicine, Amsterdam, The Netherlands.
Peter Marinus van de VenAmsterdam UMC, Vrije Universiteit Amsterdam, Department of Biostatistics and Epidemiology, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
Leo HeunksAmsterdam UMC, location Vrije Universiteit Amsterdam, Department of Intensive Care Medicine, Amsterdam, The Netherlands.
Pieter R TuinmanAmsterdam UMC, location Vrije Universiteit Amsterdam, Department of Intensive Care Medicine, Amsterdam, The Netherlands. p.tuinman@amsterdamumc.nl.
Amsterdam University Medical Centers · NLAmsterdam Neuroscience · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The stethoscope is used as first line diagnostic tool in assessment of patients with pulmonary symptoms. However, there is much debate about the diagnostic accuracy of this instrument. This meta-analysis aims to evaluate the diagnostic accuracy of lung auscultation for the most common respiratory pathologies. Studies concerning adult patients with respiratory symptoms are included. Main outcomes are pooled estimates of sensitivity and specificity with 95% confidence intervals, likelihood ratios (LRs), area under the curve (AUC) of lung auscultation for different pulmonary pathologies and breath sounds. A meta-regression analysis is performed to reduce observed heterogeneity. For 34 studies the overall pooled sensitivity for lung auscultation is 37% and specificity 89%. LRs and AUC of auscultation for congestive heart failure, pneumonia and obstructive lung diseases are low, LR- and specificity are acceptable. Abnormal breath sounds are highly specific for (hemato)pneumothorax in patients with trauma. Results are limited by significant heterogeneity. Lung auscultation has a low sensitivity in different clinical settings and patient populations, thereby hampering its clinical utility. When better diagnostic modalities are available, they should replace lung auscultation. Only in resource limited settings, with a high prevalence of disease and in experienced hands, lung auscultation has still a role.

Indexed as

Area Under CurveAuscultationConfidence IntervalsFemaleHeart FailureHumansLungLung Diseases, ObstructiveMalePneumoniaPneumothoraxRespiratory Tract DiseasesStethoscopes

Identifiers

PMID32355210
PMCPMC7192898
OpenAlexW3022944588

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.