Evidence map›Paper›PMID 33367518›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2021

Outbreak of Pseudomonas aeruginosa Infections from a Contaminated Gastroscope Detected by Whole Genome Sequencing Surveillance.

Alexander J Sundermann, Jieshi Chen, James K Miller, Melissa I Saul, Kathleen A Shutt, Marissa P Griffith, Mustapha M Mustapha, Chinelo Ezeonwuka, Kady Waggle, Vatsala Srinivasa and 9 more

Open access · greenAbstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

28 citing papers in PubMed, 46 citations in OpenAlex.

  1. Review
  2. Review
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  4. Real-Time Genomic Surveillance for Enhanced Healthcare Outbreak Detection and Control: Clinical and Economic Impact.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
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  11. Genomic Surveillance for Enhanced Healthcare Outbreak Detection and Control.medRxiv : the preprint server for health sciences · 2024
    Article
  12. Real-time genomic epidemiologic investigation of a multispecies plasmid-associated hospital outbreak of NDM-5-producing Enterobacterales infections.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2024
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  19. Two artificial tears outbreak-associated cases of XDRmedRxiv : the preprint server for health sciences · 2023
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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

19 authors at 4 institutions in 2 countries.

Alexander J SundermannMicrobial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.
Jieshi ChenAnton Laboratory, Carnegie Mellon University.
James K MillerAnton Laboratory, Carnegie Mellon University.
Melissa I SaulDepartment of Medicine, University of Pittsburgh School of Medicine.
Kathleen A ShuttMicrobial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.
Marissa P GriffithMicrobial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.
Mustapha M MustaphaMicrobial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.
Chinelo EzeonwukaMicrobial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.
Kady WaggleMicrobial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.
Vatsala SrinivasaMicrobial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.
Praveen KumarDepartment of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh.
A William PasculleDepartment of Pathology, University of Pittsburgh.
Ashley M AyresDepartment of Infection Prevention and Control, University of Pittsburgh Medical Center.
Graham M SnyderDivision of Infectious Diseases, University of Pittsburgh School of Medicine.
Vaughn S CooperDepartment of Microbiology and Molecular Genetics, and Center for Evolutionary Biology and Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Daria Van TyneDivision of Infectious Diseases, University of Pittsburgh School of Medicine.
Jane W MarshMicrobial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.
Artur W DubrawskiAnton Laboratory, Carnegie Mellon University.
Lee H HarrisonMicrobial Genomic Epidemiology Laboratory, Center for Genomic Epidemiology, University of Pittsburgh.
University of Pittsburgh · USCenter for Genomic Science · ITCarnegie Mellon University · USUniversity of Pittsburgh Medical Center · US

Funding

Enhanced Detection System for Healthcare-Associated Transmission of InfectionR01AI127472 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HARRISON, LEE H · 2016 to 2025
$7.6M
Genomic Epidemiology for Hospital Outbreak DetectionR21AI109459 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HARRISON, LEE H · 2014 to 2015
$437k
NIAID NIH HHS R01 AI127472NIAID NIH HHS R21 AI109459
6 · The paper itself

Abstract

backgroundTraditional methods of outbreak investigations utilize reactive whole genome sequencing (WGS) to confirm or refute the outbreak. We have implemented WGS surveillance and a machine learning (ML) algorithm for the electronic health record (EHR) to retrospectively detect previously unidentified outbreaks and to determine the responsible transmission routes.

methodsWe performed WGS surveillance to identify and characterize clusters of genetically-related Pseudomonas aeruginosa infections during a 24-month period. ML of the EHR was used to identify potential transmission routes. A manual review of the EHR was performed by an infection preventionist to determine the most likely route and results were compared to the ML algorithm.

resultsWe identified a cluster of 6 genetically related P. aeruginosa cases that occurred during a 7-month period. The ML algorithm identified gastroscopy as a potential transmission route for 4 of the 6 patients. Manual EHR review confirmed gastroscopy as the most likely route for 5 patients. This transmission route was confirmed by identification of a genetically-related P. aeruginosa incidentally cultured from a gastroscope used on 4of the 5 patients. Three infections, 2 of which were blood stream infections, could have been prevented if the ML algorithm had been running in real-time.

conclusionsWGS surveillance combined with a ML algorithm of the EHR identified a previously undetected outbreak of gastroscope-associated P. aeruginosa infections. These results underscore the value of WGS surveillance and ML of the EHR for enhancing outbreak detection in hospitals and preventing serious infections.

Indexed as

Cross InfectionPseudomonas InfectionsDisease OutbreaksGastroscopesHumansPseudomonas aeruginosaRetrospective StudiesWhole Genome Sequencinghealthcare-associated infectionsmachine learningoutbreak detectionPseudomonas aeruginosawhole genome sequencing surveillance

Identifiers

PMID33367518
PMCPMC8326550
OpenAlexW3113810990

What OpenQuestion holds

Textmetadata
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Registered trials

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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.