Evidence map›Paper›PMID 34632433›Full record

ArticleThe Lancet. Microbe2021

Identification of antibiotic pairs that evade concurrent resistance via a retrospective analysis of antimicrobial susceptibility test results.

Andrew M Beckley, Erik S Wright

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Microbe, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
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

20 citing papers in PubMed, 41 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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  5. Drug combinations targeting antibiotic resistance.npj antimicrobials and resistance · 2024
    Review
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  11. Review
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  14. Mutations inmBio · 2023
    Article
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  18. A Small KPC-2-Producing Plasmid inMicrobiology spectrum · 2022
    Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Andrew M BeckleyDepartment of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.
Erik S WrightDepartment of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA; Pittsburgh Center for Evolutionary Biology and Medicine, Pittsburgh, PA, USA.
University of Pittsburgh · US

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR001857 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2016 to 2025
$129.3M
The internship in Biomedical Research, Informatics, and Computer Science (iBRIC): Biomedical Informatics and Data Science research experiences for students from Minority Serving InstitutionsT15LM007059 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HARRY S HOCHHEISER · 1987 to 2026
$23.9M
Uncovering synergistic antibiotic cocktails with comparative genomicsDP2AI145058 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WRIGHT, ERIK SCOTT · 2018 to 2018
$2.3M
NCATS NIH HHS UL1 TR001857NIAID NIH HHS DP2 AI145058NLM NIH HHS T15 LM007059
6 · The paper itself

Abstract

backgroundSome antibiotic pairs display a property known as collateral sensitivity in which the evolution of resistance to one antibiotic increases sensitivity to the other. Alternating between collaterally sensitive antibiotics has been proposed as a sustainable solution to the problem of antibiotic resistance. We aimed to identify antibiotic pairs that could be considered for treatment strategies based on alternating antibiotics.

methodsWe did a retrospective analysis of 448 563 antimicrobial susceptibility test results acquired over a 4-year period (Jan 1, 2015, to Dec 31, 2018) from 23 hospitals in the University of Pittsburgh Medical Center (Pittsburgh, PA, USA) hospital system. We used a score based on mutual information to identify pairs of antibiotics displaying disjoint resistance, wherein resistance to one antibiotic is commonly associated with susceptibility to the other and vice versa. We applied this approach to the six most frequently isolated bacterial pathogens (

findingsWe identified 69 antibiotic pairs displaying varying degrees of disjoint resistance for subpopulations of the six bacterial species. However, disjoint resistance was rarely conserved at the species level, with only 6 (0·7%) of 875 antibiotic pairs showing evidence of disjoint resistance. Instead, more than half of antibiotic pairs (465 [53·1%] of 875) exhibited signatures of concurrent resistance, whereby resistance to one antibiotic is associated with resistance to another. We found concurrent resistance to extend to more than two antibiotics, with observed rates of resistance to three antibiotics being higher than predicted from pairwise information alone.

interpretationThe high frequency of concurrent resistance shows that bacteria have means of counteracting multiple antibiotics at a time. The almost complete absence of disjoint resistance at the species level implies that treatment strategies based on alternating between antibiotics might require subspecies level pathogen identification and be limited to a few antibiotic pairings.

fundingUS National Institutes of Health.

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialBacteriaEscherichia coliKlebsiella pneumoniaeMicrobial Sensitivity TestsRetrospective StudiesAnti-Bacterial Agents

Identifiers

PMID34632433
PMCPMC8496867
OpenAlexW3184295742

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.