Evidence map›Paper›PMID 26212560›Full record

ArticleScientific reports2015

Automated chest-radiography as a triage for Xpert testing in resource-constrained settings: a prospective study of diagnostic accuracy and costs.

R H H M Philipsen, C I Sánchez, P Maduskar, J Melendez, L Peters-Bax, J G Peter, R Dawson, G Theron, K Dheda, B van Ginneken

Abstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 3 pooled it
–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

47 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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.

R H H M PhilipsenDiagnostic Image Analysis Group, Radboud university medical center, Department of Radiology and Nuclear Medicine Internal postal code 766, 6500 HB Nijmegen, The Netherlands.
C I SánchezDiagnostic Image Analysis Group, Radboud university medical center, Department of Radiology and Nuclear Medicine Internal postal code 766, 6500 HB Nijmegen, The Netherlands.
P MaduskarDiagnostic Image Analysis Group, Radboud university medical center, Department of Radiology and Nuclear Medicine Internal postal code 766, 6500 HB Nijmegen, The Netherlands.
J MelendezDiagnostic Image Analysis Group, Radboud university medical center, Department of Radiology and Nuclear Medicine Internal postal code 766, 6500 HB Nijmegen, The Netherlands.
L Peters-BaxDepartment of Radiology and Nuclear Medicine, Radboud university medical center, Department of Radiology, Internal postal code 766 6500 HB Nijmegen, The Netherlands.
J G PeterLung Infection and Immunity Unit and Centre for Tuberculosis Research Innovation, Division of Pulmonology, Department of Medicine, University of Cape Town Lung Institute Cape Town, South Africa.
R DawsonLung Infection and Immunity Unit and Centre for Tuberculosis Research Innovation, Division of Pulmonology, Department of Medicine, University of Cape Town Lung Institute Cape Town, South Africa.
G TheronLung Infection and Immunity Unit and Centre for Tuberculosis Research Innovation, Division of Pulmonology, Department of Medicine, University of Cape Town Lung Institute Cape Town, South Africa.
K DhedaLung Infection and Immunity Unit and Centre for Tuberculosis Research Innovation, Division of Pulmonology, Department of Medicine, University of Cape Town Lung Institute Cape Town, South Africa.
B van GinnekenDiagnostic Image Analysis Group, Radboud university medical center, Department of Radiology and Nuclear Medicine Internal postal code 766, 6500 HB Nijmegen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular tests hold great potential for tuberculosis (TB) diagnosis, but are costly, time consuming, and HIV-infected patients are often sputum scarce. Therefore, alternative approaches are needed. We evaluated automated digital chest radiography (ACR) as a rapid and cheap pre-screen test prior to Xpert MTB/RIF (Xpert). 388 suspected TB subjects underwent chest radiography, Xpert and sputum culture testing. Radiographs were analysed by computer software (CAD4TB) and specialist readers, and abnormality scores were allocated. A triage algorithm was simulated in which subjects with a score above a threshold underwent Xpert. We computed sensitivity, specificity, cost per screened subject (CSS), cost per notified TB case (CNTBC) and throughput for different diagnostic thresholds. 18.3% of subjects had culture positive TB. For Xpert alone, sensitivity was 78.9%, specificity 98.1%, CSS $13.09 and CNTBC $90.70. In a pre-screening setting where 40% of subjects would undergo Xpert, CSS decreased to $6.72 and CNTBC to $54.34, with eight TB cases missed and throughput increased from 45 to 113 patients/day. Specialists, on average, read 57% of radiographs as abnormal, reducing CSS ($8.95) and CNTBC ($64.84). ACR pre-screening could substantially reduce costs, and increase daily throughput with few TB cases missed. These data inform public health policy in resource-constrained settings.

Indexed as

AdultFemaleHealth Care CostsHumansMachine LearningMaleMolecular Diagnostic TechniquesNetherlandsPattern Recognition, AutomatedPrevalenceProspective StudiesRadiography, ThoracicReproducibility of ResultsResource AllocationSensitivity and SpecificityTriage

Identifiers

PMID26212560
PMCPMC4515744

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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.