| Literature DB >> 30934725 |
Maria D'Accolti1,2, Irene Soffritti3,4, Sante Mazzacane5, Elisabetta Caselli6,7.
Abstract
Healthcare-associated infections (HAIs) affect up to 15% of all hospitalized patients, representing a global concern. Major causes include the persistent microbial contamination of hospital environment, and the growing antimicrobial-resistance (AMR) of HAI-associated microbes. The hospital environment represents in fact a reservoir of potential pathogens, continuously spread by healthcare personnel, visiting persons and hospitalized patients. The control of contamination has been so far addressed by the use of chemical-based sanitation procedures, which however have limitations, as testified by the persistence of contamination itself and by the growing AMR of hospital microbes. Here we review the results collected by a microbial-based sanitation system, inspired by the microbiome balance principles, in obtaining more effective control of microbial contamination and AMR. Whatever the sanitation system used, an important aspect of controlling AMR and HAIs relates to the ability to check any variation of a microbial population rapidly and effectively, thus effective monitoring procedures are also described.Entities:
Keywords: antimicrobial resistance; healthcare-associated infections; microbial technologies; sanitation
Mesh:
Year: 2019 PMID: 30934725 PMCID: PMC6479322 DOI: 10.3390/ijms20071535
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923
Figure 1Schematic representation of the “Bygiene” principle. Good bacteria (green) introduced from the outside counteract the colonization of the environment by potential pathogens (red).
Figure 2Probiotic Cleaning Hygiene System (PCHS) effect on microbial contamination and its antimicrobial-resistance (AMR) characteristics on hospital surfaces. (a) Six healthcare-associated infections (HAI)-associated pathogens were measured by Colony Forming Unit (CFU) count on hospital surfaces of five Italian hospitals before and after PCHS introduction; microbial load is expressed as percentage for each individual analyzed pathogen (mean values per m2 are also displayed); (b) the resistome of contaminating microbial population was analyzed by qPCR microarray before and after PCHS introduction; the most prevalent antibiotic-resistance genes are reported, and expressed as percentage reduction of genes during the PCHS phase compared to pre-PCHS phase.