“…The airborne PMs and microbial contamination in operating rooms (ORs) are highly related to human activities such as medical staffs’ posture, exchanging surgical tools, door movements, and supplying equipment to the scrubbed team during surgery (Kamar et al 2020 ; Lin et al 2020 ). For example, the 45° bending posture of medical staff could interrupt the ceiling-mounted airflow, which increases the microbial contamination at the surgical zone 10 fold compared to an upright postured colleague (Chow and Wang 2012 ).…”
Graphical abstract
In this study, a systematic procedure for establishing the relationship between particulate matter (PM) and microbial counts in four operating rooms (ORs) was developed. The ORs are located in a private hospital on the western coast of Peninsular Malaysia. The objective of developing the systematic procedure is to ensure that the correlation between the PMs and microbial counts are valid. Each of the procedures is conducted based on the ISO, IEST, and NEBB standards. The procedures involved verifying the operating parameters are air change rate, room differential pressure, relative humidity, and air temperature. Upon verifying that the OR parameters are in the recommended operating range, the measurements of the PMs and sampling of the microbes were conducted. The TSI 9510-02 particle counter was used to measure three different sizes of PMs: PM 0.5, PM 5, and PM 10. The MAS-100ECO air sampler was used to quantify the microbial counts. The present study confirms that PM 0.5 does not have an apparent positive correlation with the microbial count. However, the evident correlation of 7% and 15% were identified for both PM 5 and PM 10, respectively. Therefore, it is suggested that frequent monitoring of both PM 5 and PM 10 should be practised in an OR before each surgical procedure. This correlation approach could provide an instantaneous estimation of the microbial counts present in the OR.
“…The airborne PMs and microbial contamination in operating rooms (ORs) are highly related to human activities such as medical staffs’ posture, exchanging surgical tools, door movements, and supplying equipment to the scrubbed team during surgery (Kamar et al 2020 ; Lin et al 2020 ). For example, the 45° bending posture of medical staff could interrupt the ceiling-mounted airflow, which increases the microbial contamination at the surgical zone 10 fold compared to an upright postured colleague (Chow and Wang 2012 ).…”
Graphical abstract
In this study, a systematic procedure for establishing the relationship between particulate matter (PM) and microbial counts in four operating rooms (ORs) was developed. The ORs are located in a private hospital on the western coast of Peninsular Malaysia. The objective of developing the systematic procedure is to ensure that the correlation between the PMs and microbial counts are valid. Each of the procedures is conducted based on the ISO, IEST, and NEBB standards. The procedures involved verifying the operating parameters are air change rate, room differential pressure, relative humidity, and air temperature. Upon verifying that the OR parameters are in the recommended operating range, the measurements of the PMs and sampling of the microbes were conducted. The TSI 9510-02 particle counter was used to measure three different sizes of PMs: PM 0.5, PM 5, and PM 10. The MAS-100ECO air sampler was used to quantify the microbial counts. The present study confirms that PM 0.5 does not have an apparent positive correlation with the microbial count. However, the evident correlation of 7% and 15% were identified for both PM 5 and PM 10, respectively. Therefore, it is suggested that frequent monitoring of both PM 5 and PM 10 should be practised in an OR before each surgical procedure. This correlation approach could provide an instantaneous estimation of the microbial counts present in the OR.
“…In CFD simulations, there is a trade-off between the precision of the model and the computational cost (i.e., time of the process, size of the file and memory requirement) [ 52 , 53 ]. In this study, which involved many simulations, physics-controlled mesh was created in coarse element size, which was considered sufficient for obtaining satisfactory results.…”
Conventional hollow fiber hemodialyzers have a cylindrical shell-and-tube design. Due to their circular cross-section and radial flow distribution and collection in the headers, the flow of blood in the header as well as in the hollow fiber membranes is non-uniform. The creation of high shear stress and high shear rate zones or stagnation zones could result in problems, such as cell lysis and blood clotting. In this paper, a novel cuboid hemodialyzer design is proposed as an alternative to the conventional cylindrical hemodialyzer. The primary motivation behind the proposed design is to create uniform flow conditions and thereby minimize some of the above-mentioned adverse effects. The most salient feature of the proposed design is a cuboid shell within which the hollow fiber membrane bundle is potted. The lumen of the fibers is fed from one side using a flow distributor consisting of embedded primary and secondary channels, while the fibers are drained from the other side using a flow collector, which also has embedded primary and secondary channels. The flow characteristics of the lumen side of the cuboid hemodialyzer were compared with those of a conventional hemodialyzer based on computational fluid dynamics (CFD) simulations. The results of CFD simulations clearly indicated that the flow of liquid within the cuboid dialyzer was significantly more uniform. Consequently, the shear rate and shear stress were also more uniform. By adopting this new design, some of the problems associated with the conventional hemodialyzer design could potentially be addressed.
“… Fig. 1 Onsite sampling of a particulate matter (Tan et al 2022c ), b microbial counts (Tan et al 2022c ), c airflow volume (Kamar et al 2020 ) and d room pressure difference (Kamar et al 2020 ) …”
Section: Current Assessment Of Airflow and Particle Concentration In ...mentioning
confidence: 99%
“…Unidirectional airflow was disrupted during door opening motion Shih et al ( 2007 ) Isolation room Numerical simulation (CFD): Dynamic mesh Airflow model ~ k-ɛ Algorithm ~ SIMPLEC The opening and closing of a sliding door affected the room internal pressure and velocity distributions. These movements have also induced the air from the anteroom flow into the isolation room Kamar et al ( 2020 ) Operating room Numerical simulation (CFD): Dynamic mesh Airflow model ~ RNG k-ɛ Algorithm ~ PISO Replacing the turning bent-forearm medical staff with the stationary bent-forearm medical staff reduced the number of particles that settled on a patient by 60.9%, while substituting the turning straight-forearm medical staff with the stationary straight-forearm medical staff lowered the particle settlement by 37.5% Wong et al ( 2022 ) Operating room Numerical simulation (CFD): Dynamic mesh Airflow model ~ RNG k-ɛ Algorithm ~ PISO The increment of ceiling-mounted air supply diffuser’s area from 4.3 m 3 to 5.7 m 2 and 15.9 m 2 could reduce the particle settlement by 41% and 39%, respectively Villafruela et al ( 2016 ) Operating room Experimental (Onsite measurement of air velocity and air volume): Mechanical movement ~ Door opening and closing An operating room which initially had an overpressure of 20 Pa is not capable of preventing the penetration of adjacent air during the opening of the sliding door Kalliomäki et al ( 2016 ) Isolation room Experimental (Smoke visualisation): Mechanical movement ~ Human manikin was fixed to a small cart moving along a rail running on the floor Sliding door performed better than single hinged door under different ventilation setup. The air volume exchange across the doorway is relatively smaller when using the sliding door Kalliomäki et al ( 2015 ) Isolation room Experimental (Smoke visualisation and tracer gas measurements): Mechanical movement ~ Human manikin was fixed to a small cart moving along a rail running on the floor Based on smoke visualisation method, both sliding and hinged doors produced a detectable airflow through the doorway during the opening.…”
Section: Opportunity To Improve the Reliability Of The Current Assess...mentioning
An indoor environment in a hospital building requires a high indoor air quality (IAQ) to overcome patients’ risks of getting wound infections without interrupting the recovery process. However, several problems arose in obtaining a satisfactory IAQ, such as poor ventilation design strategies, insufficient air exchange, improper medical equipment placement and high door opening frequency. This paper presents an overview of various methods used for assessing the IAQ in hospital facilities, especially in an operating room, isolation room, anteroom, postoperative room, inpatient room and dentistry room. This review shows that both experimental and numerical methods demonstrated their advantages in the IAQ assessment. It was revealed that both airflow and particle tracking models could result in different particle dispersion predictions. The model selection should depend on the compatibility of the simulated result with the experimental measurement data. The primary and secondary forces affecting the characteristics of particle dispersion were also discussed in detail. The main contributing forces to the trajectory characteristics of a particle could be attributed to the gravitational force and drag force regardless of particle size. Meanwhile, the additional forces could be considered when there involves temperature gradient, intense light source, submicron particle, etc. The particle size concerned in a healthcare facility should be less than 20 μm as this particle size range showed a closer relationship with the virus load and a higher tendency to remain airborne. Also, further research opportunities that reflect a more realistic approach and improvement in the current assessment approach were proposed.
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