Evidence map›Paper›PMID 41089229›Full record

ArticleIJTLD open2025

Diagnostic accuracy of a commercial AI digital stethoscope for diagnosis of TB.

H Cox, Y Rani, L Nakiyingi, K A Francia, Y Xie, C Hoang, N Hapeela, G P Romero, E Nasinghe, N Van Hung and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IJTLD open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

H CoxDivision of Medical Microbiology and Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Y RaniFrontier Science Foundation, Brookline, MA, USA.
L NakiyingiMakerere University, Kampala, Uganda.
K A FranciaUniversidad Peruana Cayetano Heredia, Lima, Peru.
Y XieNew Jersey Medical School, Rutgers University, New Brunswick, NJ, USA.
C HoangNational Lung Hospital, Hanoi, Vietnam.
N HapeelaDivision of Medical Microbiology and Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
G P RomeroUniversidad Peruana Cayetano Heredia, Lima, Peru.
E NasingheMakerere University, Kampala, Uganda.
N Van HungNational Lung Hospital, Hanoi, Vietnam.
S KimFrontier Science Foundation, Brookline, MA, USA.
A Penn-NicholsonFIND, Geneva, Switzerland.
S E DormanMedical University of South Carolina, Charleston, SC, USA.
FEND-TB Consortium

Funding

FEND for TB supplement to accelerate BLINK X developmentU01AI152084 · NIAID · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI ALLAND, DAVID, DORMAN, SUSAN E · 2020 to 2024
$20.0M
NIAID NIH HHS U01 AI152084
6 · The paper itself

Abstract

backgroundImproved TB screening requires non-invasive, low-cost, and rapid diagnostics. Digital stethoscopes utilising machine-learning approaches to analyse respiratory sounds have potential.

methodsWe assessed accuracy of a commercial digital stethoscope for TB diagnosis among TB symptomatic participants. The microbiological reference standard (MRS) was sputum TB-positive on either liquid culture, solid culture, or Xpert MTB/RIF Ultra. Adults were enrolled from South Africa, Uganda, Vietnam, and Peru, with pre-defined sampling of 60 MRS-positive and 180 MRS-negative participants over two stages. Respiratory sounds from six auscultation positions on the participant's torso were analysed. The manufacturer (blinded to MRS status) provided participant scores and a test-positivity cut-off.

resultsAmong 240 participants, 135 (56%) were female, 62 (26%) living with HIV, 35 (15%) current smokers, and 31 (13%) previously treated for TB. Estimates of sensitivity and specificity, adjusted for country-stratified sampling, were 77% (95% confidence interval [CI]: 65-85) and 50% (95% CI: 43-57), respectively. Sensitivity was lower among people living with HIV and those with sputum smear-negative TB and varied by country. Testing took 5 min per participant (median, interquartile range 4-6).

conclusionThese early data suggest that further refinement of this test is warranted. The device is simple to use, is inexpensive, and can be used offline.

Indexed as

artificial intelligenceauscultationrespiratory soundsTB screeningtuberculosis

Identifiers

PMID41089229
PMCPMC12517259

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.