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光声气体监测用于测量麻醉气体污染及其对酒精消毒剂的交叉灵敏度。

Photoacoustic gas monitoring for anesthetic gas pollution measurements and its cross-sensitivity to alcoholic disinfectants.

机构信息

Department of Anesthesiology, Katholisches Klinikum Bochum, Ruhr-University Bochum, St. Josef Hospital, Gudrunstraße 56, 44791, Bochum, Germany.

Department of Life Science Engineering, University of Applied Sciences, Giessen, Germany.

出版信息

BMC Anesthesiol. 2019 Aug 9;19(1):148. doi: 10.1186/s12871-019-0822-7.

DOI:10.1186/s12871-019-0822-7
PMID:31399025
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6689173/
Abstract

BACKGROUND

Real-time photoacoustic gas monitoring is used for personnel exposure and environmental monitoring, but its accuracy varies when organic solvents such as alcohol contaminate measurements. This is problematic for anesthetic gas measurements in hospitals, because most disinfectants contain alcohol, which could lead to false-high gas concentrations. We investigated the cross-sensitivities of the photoacoustic gas monitor Innova 1412 (AirTech Instruments, LumaSense, Denmark) against alcohols and alcoholic disinfectants while measuring sevoflurane, desflurane and isoflurane in a laboratory and in hospital during surgery.

METHODS

25 mL ethyl alcohol was distributed on a hotplate. An optical filter for isoflurane was used and the gas monitor measured the 'isoflurane' concentration for five minutes with the measuring probe fixed 30 cm above the hotplate. Then, 5 mL isoflurane was added vaporized via an Anesthetic Conserving Device (Sedana Medical, Uppsala, Sweden). After one-hour measurement, 25 mL isopropyl alcohol, N-propanol, and two alcoholic disinfectants were subsequently added, each in combination with 5 mL isoflurane. The same experiment was in turn performed for sevoflurane and desflurane. The practical impact of the cross-sensitivity was investigated on abdominal surgeons who were exposed intraoperatively to sevoflurane. A new approach to overcome the gas monitor's cross-sensitivity is presented.

RESULTS

Cross-sensitivity was observed for all alcohols and its strength characteristic for the tested agent. Simultaneous uses of anesthetic gases and alcohols increased the concentrations and the recovery times significantly, especially while sevoflurane was utilized. Intraoperative measurements revealed mean and maximum sevoflurane concentrations of 0.61 ± 0.26 ppm and 15.27 ± 14.62 ppm. We replaced the cross-sensitivity peaks with the 10th percentile baseline of the anesthetic gas concentration. This reduced mean and maximum concentrations significantly by 37% (p < 0.001) and 86% (p < 0.001), respectively.

CONCLUSION

Photoacoustic gas monitoring is useful to detect lowest anesthetic gases concentrations, but cross-sensitivity caused one third falsely high measured mean gas concentration. One possibility to eliminate these peaks is the recovery time-based baseline approach. Caution should be taken while measuring sevoflurane, since marked cross-sensitivity peaks are to be expected.

摘要

背景

实时光声气体监测用于人员暴露和环境监测,但当酒精等有机溶剂污染测量时,其准确性会发生变化。这对于医院的麻醉气体测量来说是一个问题,因为大多数消毒剂都含有酒精,这可能导致气体浓度的错误升高。我们研究了光声气体监测仪 Innova 1412(AirTech Instruments,LumaSense,丹麦)对酒精和酒精消毒剂的交叉灵敏度,同时在实验室和手术中测量七氟醚、地氟醚和异氟醚。

方法

将 25 毫升乙醇分布在加热板上。使用异氟醚的光学滤波器,气体监测仪使用测量探头固定在加热板上方 30 厘米处,测量“异氟醚”浓度五分钟。然后,通过麻醉保存装置(Sedana Medical,Uppsala,瑞典)添加 5 毫升异氟醚蒸发。测量一小时后,随后分别添加 25 毫升异丙醇、正丙醇和两种酒精消毒剂,每种均与 5 毫升异氟醚混合。然后依次对七氟醚和地氟醚进行了相同的实验。还研究了交叉灵敏度对接受术中七氟醚暴露的腹部外科医生的实际影响,并提出了一种克服气体监测器交叉灵敏度的新方法。

结果

所有的醇都表现出交叉敏感性,其强度特征与所测试的药物一致。同时使用麻醉气体和醇会显著增加浓度和恢复时间,尤其是在使用七氟醚时。术中测量显示,七氟醚的平均浓度和最大浓度分别为 0.61±0.26ppm 和 15.27±14.62ppm。我们用麻醉气体浓度的第 10 百分位数基线替换了交叉敏感性峰值。这分别显著降低了 37%(p<0.001)和 86%(p<0.001)的平均浓度和最大浓度。

结论

光声气体监测对于检测最低麻醉气体浓度是有用的,但交叉灵敏度导致三分之一的测量平均气体浓度偏高。消除这些峰值的一种可能性是基于恢复时间的基线方法。在测量七氟醚时应谨慎,因为预计会出现明显的交叉灵敏度峰值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6541/6689173/78e5609f074a/12871_2019_822_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6541/6689173/ee4ede708e79/12871_2019_822_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6541/6689173/8d57fe41843e/12871_2019_822_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6541/6689173/a5b7a7592ee5/12871_2019_822_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6541/6689173/78e5609f074a/12871_2019_822_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6541/6689173/ee4ede708e79/12871_2019_822_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6541/6689173/8d57fe41843e/12871_2019_822_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6541/6689173/a5b7a7592ee5/12871_2019_822_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6541/6689173/78e5609f074a/12871_2019_822_Fig4_HTML.jpg

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