Evidence map›Paper›PMID 40297451›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Performance of Universal and Stratified Computer-Aided Detection Thresholds for Chest X-Ray-Based Tuberculosis Screening: A Cross-Sectional Diagnostic Accuracy Study.

Joowhan Sung, Peter James Kitonsa, Annet Nalutaaya, David Isooba, Susan Birabwa, Keneth Ndyabayunga, Rogers Okura, Jonathan Magezi, Deborah Nantale, Ivan Mugabi and 4 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

5 · Who and what money

Authors and funding

14 authors.

Joowhan SungJohns Hopkins University School of Medicine, Division of Infectious Diseases, Baltimore, MD, USA.ORCID 0000-0002-4726-9651
Peter James KitonsaWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.ORCID 0000-0003-2971-216X
Annet NalutaayaWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.ORCID 0000-0003-3903-303X
David IsoobaWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.
Susan BirabwaWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.
Keneth NdyabayungaWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.
Rogers OkuraWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.
Jonathan MageziWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.
Deborah NantaleWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.
Ivan MugabiWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.
Violet NakiizaWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.
David W DowdyWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.ORCID 0000-0003-0481-7475
Achilles KatambaWalimu, Uganda Tuberculosis Implementation Research Consortium, Kampala, Uganda.ORCID 0000-0002-2347-4183
Emily A KendallJohns Hopkins University School of Medicine, Division of Infectious Diseases, Baltimore, MD, USA.ORCID 0000-0002-0083-422X

Funding

RESEARCH TRAINING IN MICROBIAL DISEASEST32AI007291 · NIAID · JOHNS HOPKINS UNIVERSITY · PI JOEL N BLANKSON, Sara Elizabeth Cosgrove · 1986 to 2026
$9.1M
Hotspot versus clinic-based active case finding for TB in Uganda: A pragmatic randomized trialR01HL138728 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI David Wesley Dowdy, Emily A Kendall · 2017 to 2026
$5.4M
Optimizing Implementation of Digital X-ray with Computer-Aided Detection for Community-Based Tuberculosis ScreeningK23AI185268 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Joowhan Sung · 2024 to 2026
$591k
NHLBI NIH HHS R01 HL138728NIAID NIH HHS K23 AI185268NIAID NIH HHS T32 AI007291
6 · The paper itself

Abstract

Background: Computer-aided detection (CAD) software analyzes chest X-rays for features suggestive of tuberculosis (TB) and provides a numeric abnormality score. However, estimates of CAD accuracy for TB screening are hindered by the lack of confirmatory data among people with lower X-ray scores, including those without symptoms. Additionally, the appropriate X-ray score thresholds for obtaining further testing may vary according to population and client characteristics. Methods: We screened for TB in Ugandan individuals aged ≥15 years using portable chest X-rays with CAD (qXR v3). Participants were offered screening regardless of their symptoms. Those with X-ray scores above a threshold of 0.1 (range, 0 - 1) were asked to provide sputum for Xpert Ultra testing. We estimated the diagnostic accuracy of CAD for detecting Xpert-positive TB when using the same threshold for all individuals (under different assumptions about TB prevalence among people with X-ray scores <0.1), and compared this estimate to age- and/or sex-stratified approaches. Findings: Of 52,835 participants screened for TB using CAD, 8,949 (16.9%) had X-ray scores ≥0.1. Of 7,219 participants with valid Xpert Ultra results, 382 (5.3%) were Xpert-positive, including 81 with trace results. Assuming 0.1% of participants with X-ray scores <0.1 would have been Xpert-positive if tested, qXR had an estimated AUC of 0.92 (95% confidence interval 0.90-0.94) for Xpert-positive TB. Stratifying X-ray score thresholds according to age and sex improved accuracy; for example, at 96.1% specificity, estimated sensitivity was 75.0% for a universal threshold (of ≥0.65) versus 76.9% for thresholds stratified by age and sex (p=0.046). Interpretation: The accuracy of CAD for TB screening among all screening participants, including those without symptoms or abnormal chest X-rays, is higher than previously estimated. Stratifying X-ray score thresholds based on client characteristics such as age and sex could further improve accuracy, enabling a more effective and personalized approach to TB screening. Funding: National Institutes of Health.

Identifiers

PMID40297451
PMCPMC12036410

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.