Antimicrobial resistance and its statistical correlation with consumption in hospitals: An integrative literature review
DOI:
https://doi.org/10.33448/rsd-v11i1.24058Keywords:
Microbial sensitivity tests; Drug utilization; Correlation of data; Antibacterial drug resistance.Abstract
This integrative review aimed to determine which are the main bacteria that have positive correlations between the increase in antimicrobial consumption and the increase in bacterial resistance in hospitals. The articles were summarized through an integrative review, found in Pubmed® and Embase®, using the following search strategies: ("Microbial Sensitivity Tests"[Mesh]) AND "Hospitals"[Mesh]) AND "Drug Utilization "[Mesh] and 'drug utilization'exp AND 'hospital'exp AND 'antibiotic sensitivity'exp, respectively. Summarizing the author, year of publication, place of study, population studied, consumption assessment methodology and the statistical relationship and the positive correlations found between bacterial species or genera associated with the consumption data of a particular class of antimicrobials. The search strategies found a total of 414 articles, and after applying the inclusion criteria, there were 10 articles that met all the criteria used. The main bacteria or bacterial genera involved with positive correlations were P. aeruginosa (42.6%), E. coli (24.1%) and Acinetobacter spp. (9.3%). Since most of the positive correlations found were related to the same class, however about 48.2% were crossed. P. aeruginosa, E. coli and the genus Acinetobacter spp. stood out as the bacteria with the highest amount of positive correlations. International databases such as GLASS, can strengthen the statistical evidence of this relationship, allowing larger and more diverse samples, however they depend on international cooperation. This work can support pharmacovigilance in hospitals highlighting correlations already elucidated, thus contributing to the optimization of resources.
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Copyright (c) 2022 Paulo Monteiro Araujo; Carina da Costa Braúna; Susan Catherine Lima Lemos; Duanne Mendes Gomes; Veridiana Rebelo dos Santos; Sávio Freire da Silva; Luciano da Silva Lopes
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