Application of Mathematical Models in Combination with Monte Carlo Simulation for Prediction of Isoflurane Concentration in an Operation Room Theater
-
- ZARE SAKHVIDI Mohammad Javad
- Department of Occupational Health, Faculty of health, Shahid Sadoughi University of Medical Sciences, Iran
-
- BARKHORDARI Abolfazl
- Department of Occupational Health, Faculty of health, Shahid Sadoughi University of Medical Sciences, Iran
-
- SALEHI Maryam
- Department of Occupational Health, Faculty of health, Shahid Sadoughi University of Medical Sciences, Iran
-
- BEHDAD Shekoofeh
- Department of Anesthesiology, Shahid Sadoughi Hospital, Shahid Sadoughi University of Medical Sciences, Iran
-
- FALLAHZADEH Hossein
- Department of Epidemiology and Biostatistics, Faculty of Health, Shahid Sadoughi University of Medical Sciences, Iran
この論文をさがす
抄録
Applicability of two mathematical models in inhalation exposure prediction (well mixed room and near field-far field model) were validated against standard sampling method in one operation room for isoflurane. Ninety six air samples were collected from near and far field of the room and quantified by gas chromatography-flame ionization detector. Isoflurane concentration was also predicted by the models. Monte Carlo simulation was used to incorporate the role of parameters variability. The models relatively gave more conservative results than the measurements. There was no significant difference between the models and direct measurements results. There was no difference between the concentration prediction of well mixed room model and near field far field model. It suggests that the dispersion regime in room was close to well mixed situation. Direct sampling showed that the exposure in the same room for same type of operation could be up to 17 times variable which can be incorporated by Monte Carlo simulation. Mathematical models are valuable option for prediction of exposure in operation rooms. Our results also suggest that incorporating the role of parameters variability by conducting Monte Carlo simulation can enhance the strength of prediction in occupational hygiene decision making.
収録刊行物
-
- Industrial health
-
Industrial health 51 (5), 545-551, 2013
独立行政法人 労働者健康安全機構 労働安全衛生総合研究所
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1390001204280613376
-
- NII論文ID
- 130004828699
-
- NII書誌ID
- AA00672955
-
- COI
- 1:STN:280:DC%2BC3sfmtlKqtg%3D%3D
-
- ISSN
- 18808026
- 00198366
-
- NDL書誌ID
- 024925628
-
- PubMed
- 23912206
-
- 本文言語コード
- en
-
- データソース種別
-
- JaLC
- NDL
- Crossref
- PubMed
- CiNii Articles
-
- 抄録ライセンスフラグ
- 使用不可