Evidence map›Paper›PMID 37894195›Full record

ArticleMicroorganisms2023

Clinical Whole-Genome Sequencing Assay for Rapid

Bennett Shaw, Benjamin von Bredow, Allison Tsan, Omai Garner, Shangxin Yang

Abstract read
In one paragraph

Article in Microorganisms, 2023. 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. Review
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

5 authors.

Bennett ShawDepartment of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA.
Benjamin von BredowDepartment of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA.ORCID 0000-0001-8924-2193
Allison TsanDepartment of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA.
Omai GarnerDepartment of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA.
Shangxin YangDepartment of Pathology and Laboratory Medicine, UCLA David Geffen School of Medicine, Los Angeles, CA 90095, USA.ORCID 0000-0001-9991-1178

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global rise of drug resistant tuberculosis has highlighted the need for improved diagnostic technologies that provide rapid and reliable drug resistance results. Here, we develop and validate a whole genome sequencing (WGS)-based test for identification of mycobacterium tuberculosis complex (MTB) drug resistance to rifampin, isoniazid, pyrazinamide, ethambutol, and streptomycin. Through comparative analysis of drug resistance results from WGS-based testing and phenotypic drug susceptibility testing (DST) of 38 clinical MTB isolates from patients receiving care in Los Angeles, CA, we found an overall concordance between methods of 97.4% with equivalent performance across culture media. Critically, prospective analysis of 11 isolates showed that WGS-based testing provides results an average of 36 days faster than phenotypic culture-based methods. We showcase the additional benefits of WGS data by investigating a suspected laboratory contamination event and using phylogenetic analysis to search for cryptic local transmission, finding no evidence of community spread amongst our patient population in the past six years. WGS-based testing for MTB drug resistance has the potential to greatly improve diagnosis of drug resistant MTB by accelerating turnaround time while maintaining accuracy and providing additional benefits for infection control, lab safety, and public health applications.

Indexed as

clinical evaluationdrug susceptibility testingMycobacterium tuberculosis complexphylogenetic relatedness analysiswhole-genome sequencing

Identifiers

PMID37894195
PMCPMC10609454

What OpenQuestion holds

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LicenceCC BY
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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.