Evidence map›Paper›PMID 41149798›Full record

ArticleMethods and protocols2025

A Six-Step Protocol for Monitoring Antimicrobial Resistance Trends Using WHONET and R: Real-World Application and R Code Integration.

Fabio Ingravalle, Antonio Vinci, Marco Ciotti, Carla Fontana, Francesca Pica, Emanuele Sebastiani, Clara Donnoli, Martino Guido Rizzo, Dario Tedesco, Silvia D'Arezzo and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Methods and protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Observational
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

13 authors.

Fabio IngravalleDepartment of Biomedicine and Prevention, Tor Vergata University of Rome, 00133 Rome, Italy.ORCID 0000-0001-6295-9848
Antonio VinciDepartment of Biomedicine and Prevention, Tor Vergata University of Rome, 00133 Rome, Italy.ORCID 0000-0002-4915-7733
Marco CiottiVirology Unit, Polyclinic Tor Vergata Foundation, 00133 Rome, Italy.ORCID 0000-0002-9943-9130
Carla FontanaMicrobiology and Biobank Unit, National Institute for Infectious Diseases "Lazzaro Spallanzani", IRCCS, 00149 Rome, Italy.ORCID 0000-0003-2198-1947
Francesca PicaDepartment of Experimental Medicine, Tor Vergata University of Rome, 00133 Rome, Italy.ORCID 0000-0002-7899-889X
Emanuele SebastianiDepartment of Biomedicine and Prevention, Tor Vergata University of Rome, 00133 Rome, Italy.ORCID 0009-0002-0475-593X
Clara DonnoliResearch and International Relations Unit, Italian National Agency for Regional Healthcare Services, 00187 Rome, Italy.
Martino Guido RizzoDepartment of Public Health and Infectious Diseases, Sapienza University of Rome, 00185 Rome, Italy.
Dario TedescoDepartment of Innovation in Healthcare and Social Services, Emilia Romagna Region, 40127 Bologna, Italy.
Silvia D'ArezzoMicrobiology and Biobank Unit, National Institute for Infectious Diseases "Lazzaro Spallanzani", IRCCS, 00149 Rome, Italy.ORCID 0000-0002-7783-6194
Stefania CicaliniSystemic and Immune Depression-Associated Infections Unit, National Institute for Infectious Diseases "Lazzaro Spallanzani", IRCCS, 00149 Rome, Italy.ORCID 0000-0002-0754-6917
Michele Tancredi LoiudiceResearch and International Relations Unit, Italian National Agency for Regional Healthcare Services, 00187 Rome, Italy.ORCID 0009-0001-0320-3108
Massimo MauriciDepartment of Biomedicine and Prevention, Tor Vergata University of Rome, 00133 Rome, Italy.ORCID 0000-0001-5884-161X

Funding

Ministero della Salute RRC202523685965
6 · The paper itself

Abstract

Antimicrobial resistance is a global health issue, and the WHO has made significant efforts in the development of tools for its monitoring. However, such tools are underutilized, due to limited knowledge, technical capacity, and scarcity of economic resources. AMR surveillance can be conducted using WHOnet and R, two free-of-charge software tools widely adopted in both clinical practice and scientific research. WHOnet is designed for managing laboratory data and antimicrobial susceptibility test results, while R is a programming language dedicated to statistical computing and data visualization. The combined use of these tools enables a reproducible workflow for retrospective AMR trend analysis. This paper provides step-by-step instructions on how to perform such analysis and also provides the respective R code. The described code and software results are shown using real-world data from an Italian hospital as an example. The standardization of the analysis process and the rapid availability of data on antimicrobial resistance are critical for both clinicians and public health professionals. They would allow for empirical decisions on antimicrobial treatment based on the specific epidemiological characteristics of the hospital or community setting.

Indexed as

antimicrobial resistancemicrobiology laboratory dataopen-source toolsR programmingsurveillance

Identifiers

PMID41149798
PMCPMC12566455

What Socratic 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 Socratic graph.