Evidence map›Paper›PMID 40520028›Full record

ArticleJAC-antimicrobial resistance2025

Exploring variability in antibiograms: a cross-sectional study.

Valerie Leung, Marwah Alameri, Huda Almohri, Kevin A Brown, Nick Daneman, Julianne V Kus, Larissa M Matukas, Kevin L Schwartz, Bradley J Langford

Abstract read
In one paragraph

Article in JAC-antimicrobial resistance, 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. 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

9 authors.

Valerie LeungCommunicable Disease Control, Public Health Ontario, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-6780-5378
Marwah AlameriLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.
Huda AlmohriDepartment of Microbiology, LifeLabs Medical Laboratory, Toronto, ON, Canada.
Kevin A BrownCommunicable Disease Control, Public Health Ontario, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-1483-2188
Nick DanemanCommunicable Disease Control, Public Health Ontario, Toronto, ON, Canada.
Julianne V KusMicrobiology & Laboratory Services, Public Health Ontario, Toronto, ON, Canada.
Larissa M MatukasDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
Kevin L SchwartzCommunicable Disease Control, Public Health Ontario, Toronto, ON, Canada.ORCID https://orcid.org/0000-0002-3666-7005
Bradley J LangfordCommunicable Disease Control, Public Health Ontario, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-5467-6776

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Antibiograms are important tools for guiding empirical antimicrobial prescribing and monitoring antimicrobial resistance (AMR); however, there are challenges to their implementation and interpretation in practice. Variable formatting may be a contributing factor. This study explores variability in antibiogram data presentation to identify opportunities for improvement. Methods: Antibiograms from hospitals in Ontario were evaluated by visual inspection for general formatting and style, organism-specific data presentation and stratification based on CLSI M39 guidelines (Fifth Edition, 2022) and relevant literature. Hospitals were categorized by type and descriptive analysis was performed. Results: Forty-three antibiograms from 60 hospitals were included: 33.3% were large community; 26.7% were academic teaching; 20% were small community; 11.7% were medium community; and 8.5% were complex continuing care/rehabilitation facilities. All antibiograms reported at least 1 year of data, with 26.5% aggregating data from multiple facilities. Most either reported on organisms with at least 30 isolates (23.2%) or included a statement about interpretation of small numbers (69.8%). Only 27.9% included a statement about exclusion of duplicates, and 18.6% included guidance on how to use the antibiogram. Data were reported separately for Conclusions: There is significant variability in antibiogram data presentation across Ontario hospitals. Additional format standardization may help improve use for clinical decision-making and monitoring of AMR trends.

Identifiers

PMID40520028
PMCPMC12163904

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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.