Evidence map›Paper›PMID 34259555›Full record

ArticlemSphere2021

Multidimensional Clinical Surveillance of Pseudomonas aeruginosa Reveals Complex Relationships between Isolate Source, Morphology, and Antimicrobial Resistance.

Laura J Dunphy, Glynis L Kolling, Matthew L Jenior, Joanne Carroll, April E Attai, Farzad Farnoud, Amy J Mathers, Molly A Hughes, Jason A Papin

Abstract read
In one paragraph

Article in mSphere, 2021. 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. Article
  3. Review
  4. β-Lactamase diversity inAntimicrobial agents and chemotherapy · 2025
    Article
  5. Applying a polysaccharide lyase fromApplied and environmental microbiology · 2025
    Article
  6. Article
  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

9 authors.

Laura J DunphyDepartment of Biomedical Engineering, University of Virginiagrid.27755.32, Charlottesville, Virginia, USA.
Glynis L KollingDepartment of Biomedical Engineering, University of Virginiagrid.27755.32, Charlottesville, Virginia, USA.
Matthew L JeniorDepartment of Biomedical Engineering, University of Virginiagrid.27755.32, Charlottesville, Virginia, USA.
Joanne CarrollClinical Microbiology Laboratory, Department of Pathology, University of Virginiagrid.27755.32 Health System, Charlottesville, Virginia, USA.
April E AttaiClinical Microbiology Laboratory, Department of Pathology, University of Virginiagrid.27755.32 Health System, Charlottesville, Virginia, USA.
Farzad FarnoudDepartment of Electrical and Computer Engineering, University of Virginiagrid.27755.32, Charlottesville, Virginia, USA.
Amy J MathersDivision of Infectious Diseases and International Health, Department of Medicine, University of Virginiagrid.27755.32, Charlottesville, Virginia, USA.
Molly A HughesDivision of Infectious Diseases and International Health, Department of Medicine, University of Virginiagrid.27755.32, Charlottesville, Virginia, USA.
Jason A PapinDepartment of Biomedical Engineering, University of Virginiagrid.27755.32, Charlottesville, Virginia, USA.

Funding

Multi-scale model of microbial phenotype modulation by mucinsR01AI154242 · NIAID · UNIVERSITY OF VIRGINIA · PI FORD, ROSEANNE, PAPIN, JASON · 2020 to 2024
$3.1M
A unique strategy for reshaping the antibiotics model: chemokine-inspired therapeutics for targeting the host and pathogen to counter infections caused by multidrug-resistant bacteriaR01AI150941 · NIAID · UNIVERSITY OF VIRGINIA · PI HUGHES, MOLLY A · 2020 to 2024
$3.1M
Interdisciplinary Training in Systems & Biomolecular Data ScienceT32GM145443 · NIGMS · UNIVERSITY OF VIRGINIA · PI Kevin A Janes, Jason Papin · 2022 to 2026
$1.5M
Network Analysis of Pathogenicity in Pseudomonas aeruginosaR01GM088244 · NIGMS · UNIVERSITY OF VIRGINIA · PI PAPIN, JASON · 2010 to 2014
$1.5M
NIAID NIH HHS R01 AI150941NIAID NIH HHS R01 AI154242NIGMS NIH HHS R01 GM088244NIGMS NIH HHS T32 GM145443
6 · The paper itself

Abstract

Antimicrobial susceptibility in Pseudomonas aeruginosa is dependent on a complex combination of host and pathogen-specific factors. Through the profiling of 971 clinical P. aeruginosa isolates from 590 patients and collection of paired patient metadata, we show that antimicrobial resistance is associated with not only patient-centric factors (e.g., cystic fibrosis and antipseudomonal prescription history) but also microbe-specific phenotypes (e.g., mucoid colony morphology). Additionally, isolates from different sources (e.g., respiratory tract, urinary tract) displayed rates of antimicrobial resistance that were correlated with source-specific antimicrobial prescription strategies. Furthermore, isolates from the same patient often displayed a high degree of heterogeneity, highlighting a key challenge facing personalized treatment of infectious diseases. Our findings support novel relationships between isolate and patient-level data sets, providing a potential guide for future antimicrobial treatment strategies.

Indexed as

Drug Resistance, Multiple, BacterialAdolescentAdultAgedAnti-Bacterial AgentsChildChild, PreschoolCross InfectionFemaleHumansInfantMaleMicrobial Sensitivity TestsMiddle AgedPhenotypePseudomonas aeruginosaAnti-Bacterial AgentsVirulence Factorsantimicrobial resistanceclinical risk factorsinfectious diseasePseudomonas aeruginosa

Identifiers

PMID34259555
PMCPMC8386403

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.