Effect of a portable ultra-clean exponential airflow unit on the particle distribution in an operating room

The effects of a mobile laminar airflow unit on the concentration, deposition and distribution of bacteria-carrying particles in an operating room are investigated. The exploration is carried out using numerical calculation schemes (computational fluid dynamics approach). The model validation was performed through result comparisons with published measurement data from literature. Two types of mobile screen units were evaluated as an extension of turbulent-mixing operating-room ventilation. Airborne particle concentration/sedimentation was recorded with and without a screen unit on the operating table and two instrument tables. Both active and passive air sampling were examined and the results are compared. It was found that the additional mobile ultra-clean laminar airflow unit reduces the counts of airborne bacteria and surface contamination to a level acceptable for infection-prone surgeries.

[1]  William A Rutala,et al.  Control of Healthcare-Associated Staphylococcus aureus Survey of Practices in North Carolina Hospitals , 2009, Infection Control & Hospital Epidemiology.

[2]  Biagio Moretti,et al.  Air sampling methods to evaluate microbial contamination in operating theatres: results of a comparative study in an orthopaedics department. , 2012, The Journal of hospital infection.

[3]  D. Vesley,et al.  Bacterial dispersion in relation to operating room clothing , 1976, Journal of Hygiene.

[4]  A Landrin,et al.  Monitoring air sampling in operating theatres: can particle counting replace microbiological sampling? , 2005, The Journal of hospital infection.

[5]  S. A. Morsi,et al.  An investigation of particle trajectories in two-phase flow systems , 1972, Journal of Fluid Mechanics.

[6]  A Tammelin,et al.  Single-use surgical clothing system for reduction of airborne bacteria in the operating room. , 2013, The Journal of hospital infection.

[7]  S Friberg,et al.  The addition of a mobile ultra-clean exponential laminar airflow screen to conventional operating room ventilation reduces bacterial contamination to operating box levels. , 2003, The Journal of hospital infection.

[8]  J. Tinkler,et al.  The importance of airborne bacterial contamination of wounds. , 1982, The Journal of hospital infection.

[9]  B Friberg,et al.  Inconsistent correlation between aerobic bacterial surface and air counts in operating rooms with ultra clean laminar air flows: proposal of a new bacteriological standard for surface contamination. , 1999, The Journal of hospital infection.

[10]  A. Hambraeus,et al.  Aerobiology in the operating room--a review. , 1988, The Journal of hospital infection.

[11]  Eckart Meiburg,et al.  THE ACCUMULATION AND DISPERSION OF HEAVY PARTICLES IN FORCED TWO-DIMENSIONAL MIXING LAYERS. I: THE FUNDAMENTAL AND SUBHARMONIC CASES , 1994 .

[12]  Maria Teresa Montagna,et al.  Air sampling procedures to evaluate microbial contamination: a comparison between active and passive methods in operating theatres , 2012, BMC Public Health.

[13]  D. Pittet,et al.  Environmental controls in operating theatres. , 2002, The Journal of hospital infection.

[14]  C Pasquarella,et al.  A mobile laminar airflow unit to reduce air bacterial contamination at surgical area in a conventionally ventilated operating theatre. , 2007, The Journal of hospital infection.

[15]  L G Burman,et al.  Further bacteriological evaluation of the TOUL mobile system delivering ultra-clean air over surgical patients and instruments. , 2006, The Journal of hospital infection.

[16]  Sture Holmberg,et al.  Influence of staff number and internal constellation on surgical site infection in an operating room , 2014 .

[17]  Kenneth Todar Bacterial Resistance to Antibiotics , 2000 .

[18]  Annette Erichsen Andersson,et al.  Patients' experiences of acquiring a deep surgical site infection: an interview study. , 2010, American journal of infection control.

[19]  Tin-Tai Chow,et al.  Performance of ventilation system in a non-standard operating room , 2003 .

[20]  Qingyan Chen,et al.  Experimental measurements and numerical simulations of particle transport and distribution in ventilated rooms , 2006 .

[21]  T. Chow,et al.  Ventilation performance in the operating theatre against airborne infection: numerical study on an ultra-clean system. , 2005, The Journal of hospital infection.

[22]  S. Orszag,et al.  Development of turbulence models for shear flows by a double expansion technique , 1992 .

[23]  B Friberg,et al.  Mobile zoned/exponential LAF screen: a new concept in ultra-clean air technology for additional operating room ventilation. , 2002, The Journal of hospital infection.

[24]  S. Petti,et al.  [Comparison between different methods to monitor the microbial level of indoor air contamination in the dental office]. , 2003, Annali di igiene : medicina preventiva e di comunita.

[25]  G. Laurell,et al.  The relative importance of the routes and sources of wound contamination during general surgery. II. Airborne. , 1991, The Journal of hospital infection.

[26]  Cathy A Petti,et al.  Postoperative bacteremia secondary to surgical site infection. , 2002, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[27]  Gary R Seabrook,et al.  Molecular epidemiology of microbial contamination in the operating room environment: Is there a risk for infection? , 2005, Surgery.

[28]  Jianlei Niu,et al.  Modeling particle dispersion and deposition in indoor environments , 2007, Atmospheric Environment.

[29]  Bin Zhao,et al.  Comparison of indoor aerosol particle concentration and deposition in different ventilated rooms by numerical method , 2004 .

[30]  Joshua A Urban,et al.  Cost analysis of surgical site infections. , 2006, Surgical infections.

[31]  W. Sayer,et al.  Hospital airborne bacteria as estimated by the Andersen sampler versus the gravity settling culture plate. , 1972, American journal of clinical pathology.

[32]  O M LIDWELL,et al.  The size distribution of airborne particles carrying micro-organisms , 1963, Epidemiology and Infection.

[33]  A. Lai,et al.  Modeling particle distribution and deposition in indoor environments with a new drift–flux model , 2006 .

[34]  Qingyan Chen COMPARISON OF DIFFERENT k-ε MODELS FOR INDOOR AIR FLOW COMPUTATIONS , 1995 .

[35]  B Friberg,et al.  Correlation between surface and air counts of particles carrying aerobic bacteria in operating rooms with turbulent ventilation: an experimental study. , 1999, The Journal of hospital infection.

[36]  Yi Jiang,et al.  Using large eddy simulation to study particle motions in a room. , 2005, Indoor air.

[37]  P Borella,et al.  Risk factors for particulate and microbial contamination of air in operating theatres. , 2007, The Journal of hospital infection.

[38]  P. Jalovaara,et al.  Air bacterial and particle counts in total hip replacement operations using non-woven and cotton gowns and drapes. , 1989, The Journal of hospital infection.

[39]  R Lundholm,et al.  Assessment of horizontal laminar air flow instrument table for additional ultraclean space during surgery. , 2010, The Journal of hospital infection.

[40]  W C Noble,et al.  Dispersal of skin microorganisms * , 1975, The British journal of dermatology.