Evidence map›Paper›PMID 29229490›Full record

ArticleThe Journal of hospital infection2018

Pseudomonas aeruginosa intensive care unit outbreak: winnowing of transmissions with molecular and genomic typing.

B J Parcell, K Oravcova, M Pinheiro, M T G Holden, G Phillips, J F Turton, S H Gillespie

Abstract read
In one paragraph

Article in The Journal of hospital infection, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Long-Term Environmental Surveillance ofPathogens (Basel, Switzerland) · 2026
    Article
  2. Article
  3. Carbapenem-ResistantAntibiotics (Basel, Switzerland) · 2025
    Review
  4. Article
  5. Rapid Drug Susceptibility Testing to Preserve Antibiotics.Methods in molecular biology (Clifton, N.J.) · 2024
    Review
  6. Application of Pathogen Genomics to Outbreak Investigation.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. New Variants of PseudomonasMicroorganisms · 2022
    Article
  11. Article
  12. Article
  13. Field Grand Challenge Frontiers in Antibiotics.Frontiers in antibiotics · 2022
    Article
  14. Article
  15. β-lactam Resistance inPathogens (Basel, Switzerland) · 2021
    Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

7 authors.

B J ParcellNinewells Hospital & Medical School, Dundee, UK. Electronic address: b.parcell@nhs.net.
K OravcovaSchool of Medicine, University of St Andrews, St Andrews, UK.
M PinheiroSchool of Medicine, University of St Andrews, St Andrews, UK.
M T G HoldenSchool of Medicine, University of St Andrews, St Andrews, UK.
G PhillipsNinewells Hospital & Medical School, Dundee, UK.
J F TurtonAntimicrobial Resistance and Healthcare Associated Infections Reference Unit, Public Health England, Colindale, UK.
S H GillespieSchool of Medicine, University of St Andrews, St Andrews, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPseudomonas aeruginosa healthcare outbreaks can be time consuming and difficult to investigate. Guidance does not specify which typing technique is most practical for decision-making.

aimTo explore the usefulness of whole-genome sequencing (WGS) in the investigation of a P. aeruginosa outbreak, describing how it compares with pulsed-field gel electrophoresis (PFGE) and variable number tandem repeat (VNTR) analysis.

methodsSix patient isolates and six environmental samples from an intensive care unit (ICU) positive for P. aeruginosa over two years underwent VNTR, PFGE and WGS.

findingsVNTR and PFGE were required to fully determine the potential source of infection and rule out others. WGS results unambiguously distinguished linked isolates, giving greater assurance of the transmission route between wash-hand basin water and two patients, supporting the control measures employed.

conclusionWGS provided detailed information without the need for further typing. When allied to epidemiological information, WGS can be used to understand outbreak situations rapidly and with certainty. Implementation of WGS in real-time would be a major advance in day-to-day practice. It could become a standard of care as it becomes more widespread due to its reproducibility and lower costs.

Indexed as

Disease OutbreaksCross InfectionDisease Transmission, InfectiousElectrophoresis, Gel, Pulsed-FieldHumansIntensive Care UnitsMinisatellite RepeatsMolecular EpidemiologyMolecular TypingPseudomonas aeruginosaPseudomonas InfectionsWhole Genome SequencingOutbreakPseudomonas spp.ResistanceSequencingWater

Identifiers

PMID29229490
PMCPMC5840502

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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.