Application of predictive models for estimation of health care workers exposure to sevoflurane.

OBJECTIVES: The aim of this study was to assess the potential use of predictive models to estimate professional exposure to chemicals in the workplace, such as the operating room, by simultaneous determination of the levels of exposure using a model and measurements. METHODS: Measurements included determinations of sevoflurane (SEV) in the workplace air of 117 operating rooms of 31 hospitals in one Polish region. Measurements were carried out at the time of various surgical procedures during administration of anaesthetics by endotracheal intubation. The measurement results were compared with the values estimated using two models: ECETOC TRA and Stoffenmanager. RESULTS: In one case the ECETOC TRA estimated the exposure concentration almost equal to the measured concentration but, because of the need to maintain a margin of safety in case of modelling, it can be concluded that the model underestimated the concentration. The Stoffenmanager model provided accurate exposure estimates in the examined case, and it can be used as a screening tool for the assessment of occupational inhalation exposure of medical personnel to anaesthetics. CONCLUSIONS: The results are of particular importance to the circumstances in Eastern Europe, where the levels of anaesthetics often exceed the relevant occupational exposure limits.

[Application of predictive model to estimate concentrations of chemical substances in the work environment]. / Zastosowanie modelu predykcyjnego do szacowania wielkosci stezen wybranych substancji chemicznych w powietrzu srodowiska pracy.

BACKGROUND: Based on the Estimation and Assessment of Substance Exposure (EASE) predictive model implemented into the European Union System for the Evaluation of Substances (EUSES 2.1.), the exposure to three chosen organic solvents: toluene, ethyl acetate and acetone was estimated and compared with the results of measurements in workplaces. MATERIAL AND METHODS: Prior to validation, the EASE model was pretested using three exposure scenarios. The scenarios differed in the decision tree of pattern of use. Five substances were chosen for the test: 1,4-dioxane tert-methyl-butyl ether, diethylamine, 1,1,1-trichloroethane and bisphenol A. After testing the EASE model, the next step was the validation by estimating the exposure level and comparing it with the results of measurements in the workplace. We used the results of measurements of toluene, ethyl acetate and acetone concentrations in the work environment of a paint and lacquer factory, a shoe factory and a refinery. Three types of exposure scenarios, adaptable to the description of working conditions were chosen to estimate inhalation exposure. RESULTS: Comparison of calculated exposure to toluene, ethyl acetate and acetone with measurements in workplaces showed that model predictions are comparable with the measurement results. Only for low concentration ranges, the measured concentrations were higher than those predicted. CONCLUSIONS: EASE is a clear, consistent system, which can be successfully used as an additional component of inhalation exposure estimation. If the measurement data are available, they should be preferred to values estimated from models. In addition to inhalation exposure estimation, the EASE model makes it possible not only to assess exposure-related risk but also to predict workers' dermal exposure.