Evidence map›Paper›PMID 28438139›Full record

ArticleBMC infectious diseases2017

Digital CXR with computer aided diagnosis versus symptom screen to define presumptive tuberculosis among household contacts and impact on tuberculosis diagnosis.

Monde Muyoyeta, Nkatya Chanda Kasese, Deborah Milimo, Isaac Mushanga, Mapopa Ndhlovu, Nathan Kapata, Maureen Moyo-Chilufya, Helen Ayles

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 pooled it
1.5field-weighted citation impact, top 20% 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.

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

19 citing papers in PubMed, 3 syntheses or guidelines pooled it, 28 citations in OpenAlex.

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  10. Knowledge, attitudes and practices on childhood TB among healthcare workers.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
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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

8 authors at 3 institutions in 2 countries.

Monde MuyoyetaZAMBART Project, University of Zambia, School of Medicine, Lusaka, Zambia. MondeMuy@gmail.com.
Nkatya Chanda KaseseZAMBART Project, University of Zambia, School of Medicine, Lusaka, Zambia.
Deborah MilimoZAMBART Project, University of Zambia, School of Medicine, Lusaka, Zambia.
Isaac MushangaZAMBART Project, University of Zambia, School of Medicine, Lusaka, Zambia.
Mapopa NdhlovuZAMBART Project, University of Zambia, School of Medicine, Lusaka, Zambia.
Nathan KapataNational TB program, Ministry of Health, Lusaka, Zambia.
Maureen Moyo-ChilufyaZAMBART Project, University of Zambia, School of Medicine, Lusaka, Zambia.
Helen AylesZAMBART Project, University of Zambia, School of Medicine, Lusaka, Zambia.
University of Zambia · ZMLondon School of Hygiene & Tropical Medicine · GBMinistry of Health · ZM

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHousehold (HH) contact tracing is a strategy that targets high risk groups for TB. Symptom based screening is the standard used to identify HH contacts at risk for TB during HH contact tracing for TB. However, this strategy may be limited due to poor performance in predicting TB. The objective of this study was to compare CXR with Computer Aided Diagnosis (CAD) against symptom screen for defining presumptive TB and how TB detection changes with each method.

methodsHousehold contacts of consecutive index bacteriologically confirmed TB cases were visited by study teams and given TB/HIV education to raise awareness of the risk of TB following close contact with a TB patient. Contacts were encouraged to visit the health facility for screening; where symptoms history was obtained and opt out HIV testing was provided as part of the screening process. CXR was offered to all regardless of symptoms, followed by definitive sputum test with either Xpert MTB RIF or smear microscopy.

resultsAmong 919 HH contacts that presented for screening, 865 were screened with CXR and 464 (53.6%) had an abnormal CXR and the rest had a normal CXR. Among 444 HH contacts with valid sputum results, 274 (61.7%) were symptom screen positive and 255 (57.4%) had an abnormal CXR. Overall, TB was diagnosed in 32/444 (7.2%); 13 bacteriologically unconfirmed and 19 bacteriologically confirmed. Of 19 bacteriologically confirmed TB 8 (42.1%) were symptom screen negative contacts with an abnormal CXR and these 6/8 (75.0%) were HIV positive. Among the 13 bacteriologically unconfirmed TB cases, 7 (53.8%) were HIV positive and all had an abnormal CXR.

conclusionSymptom screen if used alone with follow on definitive TB testing only for symptom screen positive individuals would have missed eight of the 19 confirmed TB cases detected in this study. There is need to consider use of other screening strategies apart from symptom screen alone for optimal rule out of TB especially in HIV positive individuals that are at greatest risk of TB and present atypically.

Indexed as

Contact TracingAdolescentAdultChildFamily CharacteristicsFemaleHumansImage Interpretation, Computer-AssistedMaleMass Chest X-RayMass ScreeningMycobacterium tuberculosisPredictive Value of TestsSensitivity and SpecificitySputumTuberculosisCADDiagnosisDigital CXRHousehold contactIPTScreeningTuberculosisZambia

Identifiers

PMID28438139
PMCPMC5402643
OpenAlexW2609521275

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.