Bacterial multidrug resistance has been a serious issue for healthcare systems in recent decades, responsible for many infections and deaths. Due to the increasing incidence of antimicrobial resistance and scarce… Click to show full abstract
Bacterial multidrug resistance has been a serious issue for healthcare systems in recent decades, responsible for many infections and deaths. Due to the increasing incidence of antimicrobial resistance and scarce treatment options, research is focused on finding possible therapeutic adjuvants able to increase the efficacy of antibiotics. The aim of this article is a review of available evidence on the use of N-acetylcysteine (NAC). MEDLINE/PubMed was searched for appropriate keywords. In vitro and in vivo preclinical studies, clinical studies, reviews, and meta-analyses were retrieved and selected based on relevance. A narrative review article was written, reporting published evidence and the expert opinion of the authors. Among possible adjunctive treatments, NAC has attracted the interest of researchers as a candidate for re-purposing. It is a widely used drug with a good tolerability profile, mainly used as a mucolytic agent, with antioxidant, anti-inflammatory properties and antibacterial activity. NAC acts on different mechanisms and stages of infections, resulting in inhibition of biofilm formation, disruption of preformed biofilms, and reduction of bacterial viability. NAC may be administered as an aerosol in many types of infections, including cystic fibrosis, bronchiectasis and infective flare of chronic obstructive pulmonary disease (COPD), and by the intravenous route in severe systemic infections (including septic shock) such as those caused by carbapenemase (KPC)-producing Klebsiella pneumoniae (Kp) and Carbapenem-Resistant Acinetobacter baumannii (CR-Ab). A rationale exists for using NAC as an adjunctive treatment in multidrug-resistant (MDR) infections, based on in vitro, in vivo and clinical evidence, and future research is needed to identify candidate patients and optimal schedules for specific clinical conditions.
               
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