Evidence map›Paper›PMID 26222142›Full record

ArticlePloS one2015

Predictors for MTB Culture-Positivity among HIV-Infected Smear-Negative Presumptive Tuberculosis Patients in Uganda: Application of New Tuberculosis Diagnostic Technology.

Lydia Nakiyingi, Bareng A S Nonyane, Willy Ssengooba, Bruce J Kirenga, Damalie Nakanjako, Gloria Lubega, Pauline Byakika-Kibwika, Moses L Joloba, Jerry J Ellner, Susan E Dorman and 2 more

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Observational
  5. Article
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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

12 authors.

Lydia NakiyingiInfectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda; Department of Medicine, School of Medicine, Makerere University College of Heath Sciences, Kampala, Uganda.
Bareng A S NonyaneDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Willy SsengoobaDepartment of Medical Microbiology, Makerere University College of Heath Sciences, Kampala, Uganda.
Bruce J KirengaDepartment of Medicine, School of Medicine, Makerere University College of Heath Sciences, Kampala, Uganda.
Damalie NakanjakoInfectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda; Department of Medicine, School of Medicine, Makerere University College of Heath Sciences, Kampala, Uganda.
Gloria LubegaInfectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda.
Pauline Byakika-KibwikaInfectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda; Department of Medicine, School of Medicine, Makerere University College of Heath Sciences, Kampala, Uganda.
Moses L JolobaDepartment of Medical Microbiology, Makerere University College of Heath Sciences, Kampala, Uganda.
Jerry J EllnerBoston Medical Center, Boston University School of Medicine, Boston, MA, United States of America.
Susan E DormanDivision of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Harriet Mayanja-KizzaDepartment of Medicine, School of Medicine, Makerere University College of Heath Sciences, Kampala, Uganda.
Yukari C ManabeInfectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda; Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.

Funding

Vaccine Response and Immunotherapeutics SWGP30AI094189 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Richard E. Chaisson · 2012 to 2026
$67.0M
Medical Education for Services to All Ugandans (MESAU)R24TW008886 · FIC · MAKERERE UNIVERSITY COLLEGE OF HEALTH SCIENCES · PI SEWANKAMBO, NELSON K · 2010 to 2015
$9.2M
HIV Co-infections in Uganda: TB, Cryptococcus, and Viral Hepatitis.D43TW009771 · FIC · JOHNS HOPKINS UNIVERSITY · PI CASTELNUOVO, BARBARA, KAMBUGU, ANDREW DDUNGU · 2014 to 2023
$3.3M
Multidisciplinary Clinical Research and Mentoring in Tuberculosis DiagnosticsK24AI104830 · NIAID · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI DORMAN, SUSAN E · 2015 to 2019
$790k
FIC NIH HHS 5R24TW008886FIC NIH HHS D43 TW009771FIC NIH HHS R24 TW008886NIAID NIH HHS 1P30AI094189NIAID NIH HHS HHSN272200900050CNIAID NIH HHS K24 AI104830NIAID NIH HHS P30 AI094189PHS HHS 2722000900050C
6 · The paper itself

Abstract

backgroundThe existing World Health Organization diagnostic algorithms for smear-negative TB perform poorly in HIV-infected individuals. New TB diagnostics such as urine TB lipoarabinomannan (LAM) could improve the accuracy and reduce delays in TB diagnosis in HIV-infected smear-negative presumptive TB. We sought to determine predictors for MTB culture-positivity among these patients.

methodsThis study was nested into a prospective evaluation of HIV-infected outpatients and inpatients clinically suspected to have TB who were screened by smear-microscopy on two spot sputum samples. Data on socio-demographics, clinical symptoms, antiretroviral therapy, CXR, CD4 count, mycobacterial sputum and blood cultures and TB-LAM were collected. Logistic regression and conditional inference tree analysis were used to determine the most predictive indicators for MTB culture-positivity.

resultsOf the 418 smear-negative participants [female, 64%; median age (IQR) 32 (28-39) years, median CD4 106 (IQR 22 - 298) cells/mm3], 96/418 (23%) were sputum and/ or blood culture-positive for Mycobacterium tuberculosis (MTB) complex. Abnormal CXR (aOR 3.68, 95% CI 1.76- 7.71, p=0.001) and positive urine TB-LAM (aOR 6.21, 95% CI 3.14-12.27, p< 0.001) were significantly associated with MTB culture-positivity. Previous TB treatment (aOR 0.41, 95% CI 0.17-0.99, p=0.049) reduced the likelihood of a positive MTB culture. A conditional inference tree analysis showed that positive urine TB-LAM and abnormal CXR were the most predictive indicators of MTB culture-positivity. A combination of urine TB-LAM test and CXR had sensitivity and specificity of 50% and 86.1% respectively overall, and 70.8% and 84.1% respectively among those with CD4<100 cells/mm3.

conclusionsA positive urine TB-LAM test and an abnormal CXR significantly predict MTB culture-positivity among smear-negative HIV-infected presumptive TB patients while previous TB treatment reduces the likelihood of a positive MTB culture. Validation studies to assess the performance of diagnostic algorithms that include urine TB-LAM in the diagnosis of smear-negative TB in HIV-infected individuals are warranted.

Indexed as

Diagnostic Techniques and ProceduresAdultCulture TechniquesFemaleHIV InfectionsHumansLipopolysaccharidesMaleMycobacterium tuberculosisSensitivity and SpecificityTime FactorsTuberculosisUgandalipoarabinomannanLipopolysaccharides

Identifiers

PMID26222142
PMCPMC4519276

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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.