Comparative Evaluation of Automated, Semi-Automated, and Manual Methods for Identifying Multidrug-Resistant Enterobacteriaceae in Samples from Selected Abattoirs in Osun State, Nigeria

Abstract

In abattoirs, the Enterobacteriaceae family plays a big role in spreading antimicrobial resistance. These bacteria need proper identification for effective monitoring of resistance to antibiotics. This study looked at how well traditional manual, semi-automatic (API 20E), and fully automatic (VITEK 2) methods did when analyzing Enterobacteriaceae taken from soil and wastewater in Osun State, Nigeria.The study used a descriptive laboratory approach to analyze 101 Enterobacteria recovered from abattoirs. For analysis, 20 strains with unique traits were handpicked and tested using all three identification techniques. After calculating accuracy, sensitivity, and specificity, these were assessed for agreement using Cohen's kappa. A p-value <0.05 was considered statistically significant in this study.VITEK 2 had the best diagnostic accuracy at 100%, followed by the semi-auto API 20E at 90.0%, and the traditional methods at 75.0%. There were significant differences in accuracy among the three methods (p < 0.05). API 20E and VITEK 2 showed substantial agreement (kappa = 0.78), while the conventional methods and VITEK 2 had moderate agreement (kappa = 0.52).The automated systems clearly did better and were more reliable than the old methods for identifying Enterobacteriaceae in abattoir samples.