Use of generalized ordered logistic regression for the analysis of multidrug resistance data

Preventive Veterinary Medicine
G E Agga, H Morgan Scott

Abstract

Statistical analysis of antimicrobial resistance data largely focuses on individual antimicrobial's binary outcome (susceptible or resistant). However, bacteria are becoming increasingly multidrug resistant (MDR). Statistical analysis of MDR data is mostly descriptive often with tabular or graphical presentations. Here we report the applicability of generalized ordinal logistic regression model for the analysis of MDR data. A total of 1,152 Escherichia coli, isolated from the feces of weaned pigs experimentally supplemented with chlortetracycline (CTC) and copper, were tested for susceptibilities against 15 antimicrobials and were binary classified into resistant or susceptible. The 15 antimicrobial agents tested were grouped into eight different antimicrobial classes. We defined MDR as the number of antimicrobial classes to which E. coli isolates were resistant ranging from 0 to 8. Proportionality of the odds assumption of the ordinal logistic regression model was violated only for the effect of treatment period (pre-treatment, during-treatment and post-treatment); but not for the effect of CTC or copper supplementation. Subsequently, a partially constrained generalized ordinal logistic model was built that allows for the effe...Continue Reading

Citations

May 26, 2017·Surgical Neurology International·Ronald SahyouniJefferson W Chen
Apr 1, 2016·PloS One·Samantha RiccadonnaCesare Furlanello
Aug 19, 2020·Animals : an Open Access Journal From MDPI·Alec MichaelMaurice Pitesky

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