Feasibility of setting epidemiological cut-off values for Aeromonas spp.

This study analysed published data on the distributions of minimum inhibitory concentrations of a group of freshwater isolates classified as Aeromonas spp. with the aim of establishing whether they provided any evidence that epidemiological cut-off values set from these data would be unreliable. This group contained 233 isolates and included members of at least 11 species. The standard deviations (SDs) of the wild-type distributions for 10 antimicrobial agents were calculated for this multi-species group using the ECOFFinder and normalised resistance interpretation (NRI) algorithms. These were compared to the SDs of 110 distributions established for individual species published by the European Committee on Antimicrobial Susceptibility Testing. Fifty-one of these distributions had been generated by multiple laboratories and 59 by single laboratories. When the ECOFFinder algorithm was used to calculate the SDs, the mean for the multi-species group was 0.63 log2 µg ml-1, and the 51 individual species and multiple-laboratory groups were 0.68 and 0.65 log2 µg ml-1, respectively. When the NRI algorithm was used, the mean for the multi-species group was 0.79 log2 µg ml-1, and the 51 individual species and multiple-laboratory groups were 0.79 and 0.76 log2 µg ml-1, respectively. These comparisons indicate that the heterogeneity in the susceptibility to antimicrobial agents within the multi-species group of Aeromonas is not significantly different from that recorded for individual species. This analysis, therefore, suggests that epidemiological cut-off values designed to be applied to all members of the genus Aeromonas would not be inherently unreliable.

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Publication Details

Journal
Diseases of Aquatic Organisms
Published
2025-09-09
DOI
https://doi.org/10.3354/dao03878
Primary Topic
Aquaculture disease management and microbiota
Type
article
Field-Weighted Citation Impact
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article

Feasibility of setting epidemiological cut-off values for Aeromonas spp.

Sandrine Baron, Peter Smith, Göran Kronvall
Diseases of Aquatic Organisms
Aquaculture disease management and microbiota
article

Feasibility of setting epidemiological cut-off values for Aeromonas spp.

Sandrine Baron, Peter Smith, Göran Kronvall
article en

Abstract

This study analysed published data on the distributions of minimum inhibitory concentrations of a group of freshwater isolates classified as Aeromonas spp. with the aim of establishing whether they provided any evidence that epidemiological cut-off values set from these data would be unreliable. This group contained 233 isolates and included members of at least 11 species. The standard deviations (SDs) of the wild-type distributions for 10 antimicrobial agents were calculated for this multi-species group using the ECOFFinder and normalised resistance interpretation (NRI) algorithms. These were compared to the SDs of 110 distributions established for individual species published by the European Committee on Antimicrobial Susceptibility Testing. Fifty-one of these distributions had been generated by multiple laboratories and 59 by single laboratories. When the ECOFFinder algorithm was used to calculate the SDs, the mean for the multi-species group was 0.63 log2 µg ml-1, and the 51 individual species and multiple-laboratory groups were 0.68 and 0.65 log2 µg ml-1, respectively. When the NRI algorithm was used, the mean for the multi-species group was 0.79 log2 µg ml-1, and the 51 individual species and multiple-laboratory groups were 0.79 and 0.76 log2 µg ml-1, respectively. These comparisons indicate that the heterogeneity in the susceptibility to antimicrobial agents within the multi-species group of Aeromonas is not significantly different from that recorded for individual species. This analysis, therefore, suggests that epidemiological cut-off values designed to be applied to all members of the genus Aeromonas would not be inherently unreliable.

Diseases of Aquatic OrganismsVol. 164
Ollscoil na Gaillimhe – University of Galway (IE)
Openalex Percentile: Top 74%
Aquaculture disease management and microbiota
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