Evidence map›Paper›PMID 41254113›Full record

ArticleScientific reports2025

Funnel-based antimicrobial resistance monitoring in Italy: the FUN-IT study.

Simone Milanesi, Marta Colaneri, Sara Laura Ferrari, Alice Baratelli, Simone Villa, Elena Maria Tosca, Pier Mario Perrone, Andrea Gori, Mario Raviglione, Giuseppe De Nicolao

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Simone Milanesi *Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Marta Colaneri *Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy.
Sara Laura FerrariDepartment of Biomedical and Clinical Sciences, University of Milan, Milan, Italy.
Alice BaratelliDepartment of Biomedical and Clinical Sciences, University of Milan, Milan, Italy.
Simone VillaDepartment of Biomedical Sciences for Health, University of Milan, Milan, Italy.
Elena Maria ToscaDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Pier Mario PerroneCentre for Multidisciplinary Research in Health Science (MACH), University of Milan, Milan, Italy.
Andrea GoriDepartment of Biomedical and Clinical Sciences, University of Milan, Milan, Italy.
Mario RaviglioneCentre for Multidisciplinary Research in Health Science (MACH), University of Milan, Milan, Italy.
Giuseppe De NicolaoDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy. giuseppe.denicolao@unipv.it.ORCID http://orcid.org/0000-0002-3712-9911

Funding

Ministero dell'Università e della Ricerca PE00000007
6 · The paper itself

Abstract

Italy reports some of the highest antimicrobial resistance (AMR) rates in Europe. This necessitates multiple interventions among which improved surveillance is a key to solutions. Statistical Process Control (SPC) methods may help distinguishing between natural variability and significant regional trends. We applied specifically tailored SPC methods, namely funnel plots, Z-score charts, and chi-squared control charts to the AMR data from the AR-ISS surveillance system (2015-2023), focusing on bloodstream infections. Specifically, we analysed regional and temporal trends of carbapenem-resistant Klebsiella pneumoniae (CRKP), third-generation cephalosporin-resistant Escherichia coli (3GCephRE), carbapenem-resistant Acinetobacter spp. (CRAS), carbapenem-resistant Pseudomonas aeruginosa (CRPA), vancomycin-resistant Enterococcus faecium (VRE-faecium), and Staphylococcus aureus methicillin-resistant (MRSA). VRE- faecium showed a persistent increase at the national level, while other pathogens exhibited marked regional variability. Funnel plots identified significant outliers, particularly for CRAS and CRKP, with peaks in 2020-2021. These trends align with increased antibiotic use during the COVID-19 pandemic. The chi-squared control chart highlighted widening interregional disparities, possibly indicating an uneven distribution of AMR containment efforts across Italy. SPC methods can help highlighting significant deviations and interregional disparities in AMR trends across Italy. The identification of specific outliers suggests these tools can complement traditional surveillance approaches by flagging patterns that may warrant further investigation, supporting targeted public health interventions, especially where regional differences are pronounced.

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialCOVID-19HumansItalyAnti-Bacterial Agents

Identifiers

PMID41254113
PMCPMC12627780

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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.