Evidence map›Paper›PMID 31259025›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2019

Design and Implementation of Data Exchange Formats for Molecular Detection of Drug-Resistant Tuberculosis.

Wilfred Bonney, Sandy F Price, Roque Miramontes

Abstract read
PubMed Full text at PMC
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Wilfred BonneyData Management, Statistics and Evaluation Branch, Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Office of Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Sandy F PriceData Management, Statistics and Evaluation Branch, Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Office of Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Roque MiramontesData Management, Statistics and Evaluation Branch, Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Office of Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-resistant tuberculosis (TB) remains a public health threat to the United States and worldwide control of TB. Rapid and reliable drug susceptibility testing (DST) is essential for aiding clinicians in selecting an optimal treatment regimen for TB patients and to prevent ongoing transmission. Growth-based DST results for culture-confirmed cases are routinely reported to the U.S. Centers for Disease Control and Prevention through the National TB Surveillance System (NTSS). However, the NTSS currently lacks the capacity and functionality to accept laboratory results from advanced molecular methods that detect mutations associated with drug resistance. The objective of this study is to design and implement novel comprehensive data exchange formats that utilize the Health Level Seven (HL7) version 2.5.1 messaging hierarchy to capture, store, and monitor molecular DST data, thereby, improving the quality of data, specifications and exchange formats within the NTSS as well as ensuring full reporting of drug-resistant TB.

Identifiers

PMID31259025
PMCPMC6568111

What OpenQuestion holds

Textmetadata
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.