Real-time biofluorescent particle counting compared to conventional air sampling for monitoring airborne contamination in orthopedic implant surgery.

Journal: Antimicrobial Stewardship & Healthcare Epidemiology : ASHE
Published:
Abstract

Surgical site infection (SSI) following orthopedic surgery is a complication associated with morbidity and economic burden. Transmission of airborne bacteria that settle into surgical wounds constitutes a risk factor for SSIs. However, monitoring microbial contamination inside operating rooms with conventional methods is resource and time-consuming. This study aimed to assess correlation between a biofluorescent particle counter (BFPC) and conventional air sampling, to enable real-time monitoring of airborne contamination. Additionally, the study aimed to analyze correlation between particles near the surgical site and particles 1 meter away, to evaluate the feasibility of distance-based measurements. Correlation analysis was conducted to compare colony-forming units (CFU) collected using a Sartorius MD8 air sampler with biofluorescent viable particles detected by BioTrak 9510-BD, both positioned near the surgical site. Additionally, correlation between particle counts measured by AeroTrak 6510, positioned 1 meter away, and total particle counts measured by the BioTrak near the surgical site was evaluated. Sampling took place in two operating rooms: one with turbulent mixed airflow (TMA) and one with unidirectional airflow (UDAF). Negligible to low correlation between biofluorescent particles and CFU was observed, both in UDAF (n = 100) and TMA (n = 22). However, strong correlation was found between BFPC and particle counter measurements of total numbers of particles (Rp = 0.634-0.769, P < .001). While BFPCs offer real-time monitoring of airborne contamination, their predictive ability for CFU levels remains uncertain. Yet, the strong correlation between particles in the surgical site and particles measured 1 meter away suggests feasibility to conduct future studies with larger cohorts.

Authors
Frans Stålfelt, Josefin Seth Caous, Karin Svensson Malchau, Camilla Björn, Maziar Mohaddes