Monitoring the antimicrobial susceptibility of last-resource antimicrobials for veterinary pathogens is urgently needed from a one-health perspective. The objective of this study was to analyze the antimicrobial susceptibility trends of Spanish porcine bacteria to quinolones, cephalosporins, and polymyxins. Isolates of Actinobacillus pleuropneumoniae, Pasteurella multocida, and Escherichia coli were isolated from sick pigs from 2019 to 2022. An antimicrobial susceptibility test was determined based on the minimal inhibitory concentration (MIC) following an internationally accepted methodology. The MIC categorization was based on distributing the range of MIC values in four categories, with category one being the most susceptible (lowest MIC value) and category four the least susceptible (highest MIC value). Moreover, clinical susceptibility (susceptible/non-susceptible) was also determined according to the CLSI and EUCAST clinical breakpoints. A logistic and multinomial logistic regression model was used to analyze the susceptibility data for dichotomized and categorized MIC data, respectively, for any pair of antimicrobial/microorganism. In general terms, the antimicrobial susceptibility of pig bacteria to these antimicrobials remained stable or increased in the last four years in Spain. In the case of A. pleuropneumoniae and quinolones, a significant temporal trend was observed where isolates from 2020 had significantly increased odds of being more susceptible than isolates from 2019. In the case of E. coli and polymyxins, a significant temporal trend was observed where isolates from 2020 and 2021 had significantly increased odds of being more susceptible than isolates from 2019 and 2020, respectively. Finally, significant odds of being less susceptible were only observed for cephalosporins and E. coli for 2020 versus 2019, stagnating for the rest of study period. These results provide sound data on critically important antimicrobials in swine medicine.
Keywords: antimicrobial susceptibility; porcine pathogens; trend analysis.