The impact of VITEK 2 implementation for identification and susceptibility testing of microbial isolates in a Brazilian public hospital

Abstract

Introduction. The use of automated systems in identification and susceptibility tests can improve antimicrobial therapy, and positively impact clinical outcomes with a decrease in antimicrobial resistance, hospitalization time, costs, and mortality. Aim. The aim of this study was to evaluate the clinical impact of an automated method for identification and susceptibility testing of microbial isolates. Methodology. This was a retrospective cross-sectional study aimed to analyse the results before and after the implementation period of a VITEK 2 system in a Brazilian university hospital. Based on data from medical records, patients with a positive culture of clinical samples from January to July 2017 (conventional method) and from August to December 2017 (automated method) were included in this study. Demographic data, hospitalization time, time interval between culture collection and results, culture results and site, susceptibility profile, minimum inhibitory concentration, and outcome data were evaluated. Chi-square and Fischer’s tests were used in the analysis. Results. Of the total samples, 836 were considered valid by the inclusion criteria, with 219 patients before VITEK 2 system implementation group and 545 in the post-implementation group. The comparison between the two periods showed a reduction of 25 % of the time to culture reports, a decrease of 33.5 to 17.0 days of hospitalization, and a reduction in mortality from 44.3–31.0 %, respectively. Conclusion. The VITEK 2 system provided early access to appropriate antimicrobial therapy for patients and effected a positive clinical impact with a reduction in mortality and hospitalization time.

Antagonistic Potentiality of Actinomycete-Derived Extract with Anti-Biofilm, Antioxidant, and Cytotoxic Capabilities as a Natural Combating Strategy for Multidrug-Resistant ESKAPE Pathogens

“…Decarli et al . [ 48 ] reported that the use of automated systems in the identification of clinical species can improve antibiotic therapy and significantly impact clinical outcomes by reducing antibiotic resistance, hospitalization, costs, and mortality.…”