Evidence map›Paper›PMID 31714937›Full record

ArticlePLoS biology2019

Surveillance to maintain the sensitivity of genotype-based antibiotic resistance diagnostics.

Allison L Hicks, Stephen M Kissler, Marc Lipsitch, Yonatan H Grad

Abstract read
In one paragraph

Article in PLoS biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. The frontiers of addressing antibiotic resistance in Neisseria gonorrhoeae.Translational research : the journal of laboratory and clinical medicine · 2020
    Review
  7. 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

4 authors.

Allison L HicksDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0003-1372-1301
Stephen M KisslerDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0001-6000-8387
Marc LipsitchDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0003-1504-9213
Yonatan H GradDepartment of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0001-5646-1314

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2009 to 2018
$26.4M
Genomics approaches to elucidating pathways to antibiotic resistance in Neisseria gonorrhoeaeR01AI132606 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Yonatan H Grad · 2017 to 2026
$3.8M
NIAID NIH HHS R01 AI132606NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

The sensitivity of genotype-based diagnostics that predict antimicrobial susceptibility is limited by the extent to which they detect genes and alleles that lead to resistance. As novel resistance variants are expected to emerge, such sensitivity is expected to decline unless the new variants are detected and incorporated into the diagnostic. Here, we present a mathematical framework to define how many diagnostic failures may be expected under varying surveillance regimes and thus quantify the surveillance needed to maintain the sensitivity of genotype-based diagnostics.

Indexed as

GenotypeDrug Resistance, BacterialDrug Resistance, MicrobialEpidemiological MonitoringGenetic MarkersMicrobial Sensitivity TestsGenetic Markers

Identifiers

PMID31714937
PMCPMC6874359

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.