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Validation of genotype cluster investigations for Mycobacterium tuberculosis: application results for 44 clusters from four heterogeneous United States jurisdictions

Overview of attention for article published in BMC Infectious Diseases, October 2016
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

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1 policy source

Citations

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6 Dimensions

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36 Mendeley
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Title
Validation of genotype cluster investigations for Mycobacterium tuberculosis: application results for 44 clusters from four heterogeneous United States jurisdictions
Published in
BMC Infectious Diseases, October 2016
DOI 10.1186/s12879-016-1937-9
Pubmed ID
Authors

Larry D. Teeter, Padmaja Vempaty, Duc T. M. Nguyen, Jane Tapia, Sharon Sharnprapai, Smita Ghosh, J. Steven Kammerer, Roque Miramontes, Wendy A. Cronin, Edward A. Graviss

Abstract

Tracking the dissemination of specific Mycobacterium tuberculosis (Mtb) strains using genotyped Mtb isolates from tuberculosis patients is a routine public health practice in the United States. The present study proposes a standardized cluster investigation method to identify epidemiologic-linked patients in Mtb genotype clusters. The study also attempts to determine the proportion of epidemiologic-linked patients the proposed method would identify beyond the outcome of the conventional contact investigation. The study population included Mtb culture positive patients from Georgia, Maryland, Massachusetts and Houston, Texas. Mtb isolates were genotyped by CDC's National TB Genotyping Service (NTGS) from January 2006 to October 2010. Mtb cluster investigations (CLIs) were conducted for patients whose isolates matched exactly by spoligotyping and 12-locus MIRU-VNTR. CLIs were carried out in four sequential steps: (1) Public Health Worker (PHW) Interview, (2) Contact Investigation (CI) Evaluation, (3) Public Health Records Review, and (4) CLI TB Patient Interviews. Comparison between patients whose links were identified through the study's CLI interviews (Step 4) and patients whose links were identified earlier in CLI (Steps 1-3) was conducted using logistic regression. Forty-four clusters were randomly selected from the four study sites (401 patients in total). Epidemiologic links were identified for 189/401 (47 %) study patients in a total of 201 linked patient-pairs. The numbers of linked patients identified in each CLI steps were: Step 1 - 105/401 (26.2 %), Step 2 - 15/388 (3.9 %), Step 3 - 41/281 (14.6 %), and Step 4 - 28/119 (30 %). Among the 189 linked patients, 28 (14.8 %) were not identified in previous CI. No epidemiologic links were identified in 13/44 (30 %) clusters. We validated a standardized and practical method to systematically identify epidemiologic links among patients in Mtb genotype clusters, which can be integrated into the TB control and prevention programs in public health settings. The CLI interview identified additional epidemiologic links that were not identified in previous CI. One-third of the clusters showed no epidemiologic links despite being extensively investigated, suggesting that some improvement in the interviewing methods is still needed.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 14%
Student > Ph. D. Student 5 14%
Student > Master 4 11%
Lecturer 3 8%
Other 3 8%
Other 5 14%
Unknown 11 31%
Readers by discipline Count As %
Medicine and Dentistry 11 31%
Biochemistry, Genetics and Molecular Biology 3 8%
Nursing and Health Professions 2 6%
Agricultural and Biological Sciences 2 6%
Unspecified 1 3%
Other 2 6%
Unknown 15 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 December 2016.
All research outputs
#7,491,592
of 22,899,952 outputs
Outputs from BMC Infectious Diseases
#2,549
of 7,691 outputs
Outputs of similar age
#114,653
of 316,336 outputs
Outputs of similar age from BMC Infectious Diseases
#74
of 220 outputs
Altmetric has tracked 22,899,952 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,691 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has gotten more attention than average, scoring higher than 62% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 316,336 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 220 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.