Evidence map›Paper›PMID 39131622›Full record

ArticlePeerJ2024

Towards unified reporting of genome sequencing results in clinical microbiology.

Eugenio Mutschler, Tim Roloff, Aitana Neves, Hege Vangstein Aamot, Belén Rodriguez-Sanchez, Mario Ramirez, John Rossen, Natacha Couto, Ângela Novais, Benjamin P Howden and 6 more

Abstract read
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. 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

16 authors.

Eugenio Mutschler *Institute of Medical Microbiology, University of Zürich, Zurich, Switzerland.ORCID 0009-0008-0544-2031
Tim Roloff *Institute of Medical Microbiology, University of Zürich, Zurich, Switzerland.
Aitana NevesSwiss Institute of Bioinformatics, Geneva, Switzerland.
Hege Vangstein AamotAkershus University Hospital, Lorenskog, Norway.
Belén Rodriguez-SanchezHospital Gregorio Marañon, Madrid, Spain.
Mario RamirezInstituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.ORCID 0000-0002-4084-6233
John RossenUniversity Medical Center Groningen, Zwolle, Netherlands.ORCID 0000-0002-7167-8623
Natacha CoutoCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Ângela NovaisUCIBIO. Applied Molecular Biosciences Unit, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Porto, Portugal.ORCID 0000-0003-1171-0326
Benjamin P HowdenUniversity of Melbourne, Parkville, Australia.
Sylvain BrisseInstitut Pasteur, Paris, France.
Sandra ReuterMedical Center, University of Freiburg, Freiburg, Germany.
Oliver NolteInstitute of Medical Microbiology, University of Zürich, Zurich, Switzerland.ORCID 0000-0002-1761-0812
Adrian EgliInstitute of Medical Microbiology, University of Zürich, Zurich, Switzerland.
Helena M B Seth-SmithInstitute of Medical Microbiology, University of Zürich, Zurich, Switzerland.
ESCMID Study Group for Epidemiological Markers (ESGEM), and ESCMID Study Group for Genomic and Molecular Diagnostics (ESGMD)

Funding

University of Zurich, Switzerland
6 · The paper itself

Abstract

Whole genome sequencing (WGS) has become a vital tool in clinical microbiology, playing an important role in outbreak investigations, molecular surveillance, and identification of bacterial species, resistance mechanisms and virulence factors. However, the complexity of WGS data presents challenges in interpretation and reporting, requiring tailored strategies to enhance efficiency and impact. This study explores the diverse needs of key stakeholders in healthcare, including clinical management, laboratory work, public surveillance and epidemiology, infection prevention and control, and academic research, regarding WGS-based reporting of clinically relevant bacterial species. In order to determine preferences regarding WGS reports, human-centered design approach was employed, involving an online survey and a subsequent workshop with stakeholders. The survey gathered responses from 64 participants representing the above mentioned healthcare sectors across geographical regions. Key findings include the identification of barriers related to data accessibility, integration with patient records, and the complexity of interpreting WGS results. As the participants designed their ideal report using nine pre-defined sections of a typical WGS report, differences in needs regarding report structure and content across stakeholders became evident. The workshop discussions further highlighted the need to feature critical findings and quality metrics prominently in reports, as well as the demand for flexible report designs. Commonalities were observed across stakeholder-specific reporting templates, such as the uniform ranking of certain report sections, but preferences regarding the depth of content within these sections varied. Using these findings, we suggest stakeholder-specific structures which should be considered when designing customized reporting templates. In conclusion, this study underscores the importance of tailoring WGS-based reports of clinically relevant bacteria to meet the distinct needs of diverse healthcare stakeholders. The evolving landscape of digital reporting increases the opportunities with respect to WGS reporting and its utility in managing infectious diseases and public health surveillance.

Indexed as

Whole Genome SequencingGenome, BacterialHumansSurveys and QuestionnairesCustomised reportsDiagnosticsGenome sequencingNGSPublic healthSurveillanceTreatmentWGS

Identifiers

PMID39131622
PMCPMC11317035

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.