Evidence map›Paper›PMID 24618839›Full record

ArticlePloS one2014

The road to tuberculosis (Mycobacterium tuberculosis) elimination in Arkansas; a re-examination of risk groups.

Anna Berzkalns, Joseph Bates, Wen Ye, Leonard Mukasa, Anne Marie France, Naveen Patil, Zhenhua Yang

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Increasing likelihood of advanced pulmonary tuberculosis at initial diagnosis in a low-incidence US state.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2018
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Pulmonary Tuberculosis in a Patient with Cystic Fibrosis.North American journal of medical sciences · 2015
    Article
  12. Review
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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

7 authors.

Anna BerzkalnsDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.
Joseph BatesArkansas Department of Health, Little Rock, Arkansas, United States of America; Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America.
Wen YeDepartment of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.
Leonard MukasaArkansas Department of Health, Little Rock, Arkansas, United States of America; Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America.
Anne Marie FranceDivision of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Naveen PatilArkansas Department of Health, Little Rock, Arkansas, United States of America; College of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America.
Zhenhua YangDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study was conducted to generate knowledge useful for developing public health interventions for more effective tuberculosis control in Arkansas.

methodsThe study population included 429 culture-confirmed reported cases (January 1, 2004-December 31, 2010). Mycobacterium tuberculosis genotyping data were used to identify cases likely due to recent transmission (clustered) versus reactivation (non-clustered). Poisson regression models estimated average decline rate in incidence over time and assessed the significance of differences between subpopulations. A multinomial logistic model examined differences between clustered and non-clustered incidence.

resultsA significant average annual percent decline was found for the overall incidence of culture-confirmed (9%; 95% CI: 5.5%, 16.9%), clustered (6%; 95% CI: 0.5%, 11.6%), and non-clustered tuberculosis cases (12%; 95% CI: 7.6%, 15.9%). However, declines varied among demographic groups. Significant declines in clustered incidence were only observed in males, non-Hispanic blacks, 65 years and older, and the rural population.

conclusionsThese findings suggest that the Arkansas tuberculosis control program must target both traditional and non-traditional risk groups for successful tuberculosis elimination. The present study also demonstrates that a thorough analysis of TB trends in different population subgroups of a given geographic region or state can lead to the identification of non-traditional risk factors for TB transmission. Similar studies in other low incidence populations would provide beneficial data for how to control and eventually eliminate TB in the U.S.

Indexed as

Mycobacterium tuberculosisAdolescentAdultAgedAged, 80 and overAge DistributionAge FactorsArkansasFemaleGenotypeHumansIncidenceMaleMiddle AgedPublic Health SurveillanceRisk Factors

Identifiers

PMID24618839
PMCPMC3949677

What OpenQuestion holds

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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.