Evaluation of an Algorithm for Identifying Persistent Nasal Staphylococcus Aureus Carriage in a Cohort of Healthy Volunteers and Patients Regularly Monitored at the CHU of Saint-Etienne

Overview

The nasal carriage of Staphylococcus aureus is a major risk factor of S. aureus infection, notably in hemodialysis patients (HPs). Decolonization strategies were shown able to reduce the rate of S. aureus infection in this category of patients although the risk of emergence of antimicrobial resistance persists. Approximately one quarter of the general population is colonized by S. aureus in the anterior part of the nostril (vestibulum nasi). Three main categories of nasal carriers have been historically identified: persistent carriers (20%, 12-30%\]), intermittent carriers (30%, \[16-70%\]) and non-carriers (50% \[16-69%\]). By contrast to intermittent carriers and non-carriers, persistent nasal carriers have a higher risk of S. aureus infection, especially in continuous peritoneal dialysis and in orthopedic surgery. Persistent carriers are characterized by a higher nasal bacterial load, a longer duration of carriage, a lower rate of exchange of S. aureus strains, and a particular affinity for the carried strain. However, there is no consensual definition of this persistent carriage state. In previous studies, 5 to 12 nasal sampling episodes were realized for a period ranging from 5 weeks to 8 years. The index of carriage, corresponding to the number of samples positive for S. aureus divided by the total number of samples, has been proposed to standardize the definition of the carriage state. According to standard tools, it is almost impossible to determine the nasal carriage state in routine practice. Recently, an algorithm based on one or two quantitative cultures from nasal samples taken within 2 days that was able to distinguish accurately persistent and non-persistent nasal carriers of S. aureus has been described; only one nasal sample was needed in more than 9 cases out of 10. The aim of the present study was to assess prospectively the reliability of this algorithm in clinical practice in a cohort of healthcare workers (HCWs) and HPs and to check its ability for identifying patients with the highest risk of S. aureus infection