Systematic study on the relationship between particulate matter and microbial counts in hospital operating rooms

Huiyi Tan1, Keng Yinn Wong2,3, Bemgba Bevan Nyakuma4

  • 1School of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia.

Insights

Monitoring particulate matter (PM) in operating rooms (ORs) is crucial. This study found PM 5 and PM 10 correlate with microbial counts, suggesting regular monitoring for better OR hygiene.

Area of Science:

  • Environmental Science
  • Microbiology
  • Healthcare Engineering

Background:

  • Maintaining sterile operating room (OR) environments is critical for patient safety.
  • Particulate matter (PM) and microbial contamination are key factors affecting OR air quality.
  • Standardized procedures are needed to validate the relationship between PM and microbial levels.

Purpose of the Study:

  • To develop and validate a systematic procedure for assessing the correlation between particulate matter (PM) and microbial counts in hospital operating rooms (ORs).
  • To ensure the reliability of measurements for PM and microbial contamination in ORs.
  • To establish a basis for real-time estimation of microbial load in ORs.

Main Methods:

  • Procedures were developed adhering to ISO, IEST, and NEBB standards.
  • Key operating room parameters (air change rate, differential pressure, humidity, temperature) were verified.
  • Particulate matter (PM 0.5, PM 5, PM 10) was measured using a TSI 9510-02 particle counter.
  • Microbial counts were quantified using a MAS-100ECO air sampler.

Main Results:

  • PM 0.5 showed no significant positive correlation with microbial counts.
  • A 7% correlation was observed between PM 5 and microbial counts.
  • A 15% correlation was identified between PM 10 and microbial counts.

Conclusions:

  • PM 5 and PM 10 levels are correlated with microbial counts in operating rooms.
  • Frequent monitoring of PM 5 and PM 10 in ORs before procedures is recommended.
  • This correlation approach offers a potential method for instantaneous estimation of OR microbial load.

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