Evidence map›Paper›PMID 33150354›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2021

The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration.

Alyssa Long, Alexander Glogowski, Matthew Meppiel, Lisa De Vito, Eric Engle, Michael Harris, Grace Ha, Darren Schneider, Andrei Gabrielian, Darrell E Hurt and 1 more

Abstract read
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In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

11 authors.

Alyssa LongDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Alexander GlogowskiDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Matthew MeppielDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Lisa De VitoDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Eric EngleDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Michael HarrisDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Grace HaDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Darren SchneiderDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Andrei GabrielianDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Darrell E HurtDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.
Alex RosenthalDepartment of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveClinical research informatics tools are necessary to support comprehensive studies of infectious diseases. The National Institute of Allergy and Infectious Diseases (NIAID) developed the publicly accessible Tuberculosis Data Exploration Portal (TB DEPOT) to address the complex etiology of tuberculosis (TB). MATERIALS AND

methodsTB DEPOT displays deidentified patient case data and facilitates analyses across a wide range of clinical, socioeconomic, genomic, and radiological factors. The solution is built using Amazon Web Services cloud-based infrastructure, .NET Core, Angular, Highcharts, R, PLINK, and other custom-developed services. Structured patient data, pathogen genomic variants, and medical images are integrated into the solution to allow seamless filtering across data domains.

resultsResearchers can use TB DEPOT to query TB patient cases, create and save patient cohorts, and execute comparative statistical analyses on demand. The tool supports user-driven data exploration and fulfills the National Institute of Health's Findable, Accessible, Interoperable, and Reusable (FAIR) principles. DISCUSSION: TB DEPOT is the first tool of its kind in the field of TB research to integrate multidimensional data from TB patient cases. Its scalable and flexible architectural design has accommodated growth in the data, organizations, types of data, feature requests, and usage. Use of client-side technologies over server-side technologies and prioritizing maintenance have been important lessons learned. Future directions are dynamically prioritized and key functionality is shared through an application programming interface.

conclusionThis paper describes the platform development methodology, resulting functionality, benefits, and technical considerations of a clinical research informatics application to support increased understanding of TB.

Indexed as

InternetMedical Informatics ApplicationsTuberculosisComputational BiologyDatabases as TopicGenomicsHumansNational Institute of Allergy and Infectious Diseases (U.S.)RadiologySoftwareUnited Statesclinical research informaticscohort creationdata analysisdata integrationtuberculosis

Identifiers

PMID33150354
PMCPMC8454519

What OpenQuestion holds

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LicenceCC BY
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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.