Niccolò Vonci1, Maria F De Marco2, Anna Grasso2, Giuseppe Spataro1, Gabriele Cevenini3, Gabriele Messina4. 1. Post Graduate School of Public Health, University of Siena, Italy. 2. Medical Management, "Le Scotte" Teaching Hospital, Siena, Italy. 3. Department of Molecular and Developmental Medicine, University of Siena, Italy. 4. Department of Molecular and Developmental Medicine, University of Siena, Italy. Electronic address: gabriele.messina@unisi.it.
Abstract
BACKGROUND: Control of airborne microbial contamination is important in operating rooms (ORs). To keep airborne contamination low, guidelines should highlight the importance of air turnover. The aims of the study were: (1) to verify the association between air turnover and airborne contamination in ORs; and (2) to identify a statistical relationship between air turnover and airborne microbial contamination. METHODS: A cross sectional study was carried out from November 2014 to July 2017 in the teaching Hospital of Siena. Nineteen ORs (14 with turbulent and 5 with laminar flow ventilation) were surveyed a total of 59 times under operating conditions. Air samples were collected with an air sampler. Petri dishes, incubated at 36 °C for 48 h, were used to quantify colony forming units in the samples (CFU). The data was transformed to evaluate several statistically significant nonlinear associations between air turnover, quantified as air changes per hour (ACH) and CFU per cubic meter of air (p < 0.05). RESULTS: A log-linear regression model provided the best fit between ACH and CFU for laminar (p = 0.013; R2 = 0.3911) and turbulent flow systems (p = 0.002; R2 = 0.3443). The corresponding model was: ln(CFU) = (a - b*ACH), where the regression parameters were estimated at a = 4.02 and b = 0.037 for laminar flow and a = 5.24 and b = 0.067 for turbulent flow. CONCLUSIONS: Italian guidelines indicate microbial load limits of 20 and 180 CFU/m3 for operating rooms with laminar and turbulent flow ventilation, respectively. The model allowed us to evaluate the minimum number of ACHs to keep CFU within these limits. Ad hoc measurements in other environments can be used to calibrate the relationship between ACH and CFU.
BACKGROUND: Control of airborne microbial contamination is important in operating rooms (ORs). To keep airborne contamination low, guidelines should highlight the importance of air turnover. The aims of the study were: (1) to verify the association between air turnover and airborne contamination in ORs; and (2) to identify a statistical relationship between air turnover and airborne microbial contamination. METHODS: A cross sectional study was carried out from November 2014 to July 2017 in the teaching Hospital of Siena. Nineteen ORs (14 with turbulent and 5 with laminar flow ventilation) were surveyed a total of 59 times under operating conditions. Air samples were collected with an air sampler. Petri dishes, incubated at 36 °C for 48 h, were used to quantify colony forming units in the samples (CFU). The data was transformed to evaluate several statistically significant nonlinear associations between air turnover, quantified as air changes per hour (ACH) and CFU per cubic meter of air (p < 0.05). RESULTS: A log-linear regression model provided the best fit between ACH and CFU for laminar (p = 0.013; R2 = 0.3911) and turbulent flow systems (p = 0.002; R2 = 0.3443). The corresponding model was: ln(CFU) = (a - b*ACH), where the regression parameters were estimated at a = 4.02 and b = 0.037 for laminar flow and a = 5.24 and b = 0.067 for turbulent flow. CONCLUSIONS: Italian guidelines indicate microbial load limits of 20 and 180 CFU/m3 for operating rooms with laminar and turbulent flow ventilation, respectively. The model allowed us to evaluate the minimum number of ACHs to keep CFU within these limits. Ad hoc measurements in other environments can be used to calibrate the relationship between ACH and CFU.
Authors: Cesira Pasquarella; Carla Balocco; Maria Eugenia Colucci; Elisa Saccani; Samuel Paroni; Lara Albertini; Pietro Vitali; Roberto Albertini Journal: Int J Environ Res Public Health Date: 2020-01-10 Impact factor: 3.390
Authors: Giuliana Banche; Anna Maria Cuffini; Sara Comini; Narcisa Mandras; Maria Rita Iannantuoni; Francesca Menotti; Andrea Giuseppe Musumeci; Giorgia Piersigilli; Valeria Allizond Journal: Microbiol Spectr Date: 2021-11-10