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一种用于估计通气比格犬肺死腔以校正混合气体中呼出丙泊酚浓度的方法的验证。

Validation of a method for estimating pulmonary dead space in ventilated beagles to correct exhaled propofol concentration in mixed air.

作者信息

Li Xiaoxiao, Chang Pan, Liu Xing, Zhao Zhongjun, Duan Yixiang, Zhang Wensheng

机构信息

Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, China.

Laboratory of Anesthesia and Critical Care Medicine, National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology, West China Hospital,, Sichuan University, Chengdu, China.

出版信息

BMC Vet Res. 2025 Jan 7;21(1):9. doi: 10.1186/s12917-024-04458-1.

DOI:10.1186/s12917-024-04458-1
PMID:39773486
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11706130/
Abstract

BACKGROUND

Mixed exhaled air has been widely used to determine exhaled propofol concentrations with online analyzers, but changes in dead space proportions may lead to inaccurate assessments of critical drug concentration data. This study proposes a method to correct propofol concentration in mixed air by estimating pulmonary dead space through reconstructing volumetric capnography (Vcap) from time-CO and time-volume curves, validated with vacuum ultraviolet time-of-flight mass spectrometry (VUV-TOF MS).

METHODS

Existing monitoring parameters, including time-volume and time-CO curves, were used to determine Vcap. The ratio of physiological dead space to tidal volume (V/V) was calculated using Bohr's formula. Additionally, an animal experiment on beagles was conducted with continuous propofol administration until a pseudo-steady state in exhaled propofol concentration was achieved. The propofol concentration in mixed air (CONC), and in alveolar air combined with N (CONC) were measured using VUV-TOF MS to calculate V/V. The agreements between V/V values from the two methods, along with the predicted CONC values based on Vcap and the actual measured CONC values were evaluated using the intraclass correlation coefficient (ICC) and Pearson correlation analysis.

RESULTS

After 30 min of continuous propofol administration, a stable respiratory cycle was selected for analysis in each beagle. The calculated V/V values were 0.535 for beagle A, 0.544 for beagle B, and 0.552 for beagle C. Additionally, based on CONC and CONC, the calculated V/V values were 0.494, 0.504, and 0.513, respectively. Strong agreement between the two methods was demonstrated by an ICC of 0.994 (P = 0.003) and Pearson's r of 0.995 (P = 0.045). Additionally, the predicted CONC values from mixed exhaled air (5.11 parts per billion by volume (ppbv) for beagle A, 5.93 ppbv for beagle B, and 2.56 ppbv for beagle C) showed strong agreement with the actual CONC values, with an ICC of 0.996 (P = 0.002) and Pearson's r of 0.994 (P = 0.046).

CONCLUSION

The physiological dead space to tidal volume ratio from mixed air in beagles can be accurately measured using the existing time-volume and time-CO curves from the anesthesia machine, enabling corrections of exhaled propofol concentrations in mixed air samples.

摘要

背景

混合呼出气体已被广泛用于通过在线分析仪测定呼出丙泊酚浓度,但死腔比例的变化可能导致对关键药物浓度数据的评估不准确。本研究提出一种方法,通过从时间-二氧化碳(time-CO)和时间-容积曲线重建容积式二氧化碳图(Vcap)来估计肺死腔,从而校正混合气体中的丙泊酚浓度,并通过真空紫外飞行时间质谱(VUV-TOF MS)进行验证。

方法

利用现有的监测参数,包括时间-容积和时间-CO曲线来确定Vcap。使用玻尔公式计算生理死腔与潮气量的比值(V/V)。此外,对比格犬进行动物实验,持续输注丙泊酚直至呼出丙泊酚浓度达到伪稳态。使用VUV-TOF MS测量混合气体中的丙泊酚浓度(CONC)以及与氮气混合的肺泡气中的丙泊酚浓度(CONC),以计算V/V。使用组内相关系数(ICC)和Pearson相关分析评估两种方法得出 的V/V值之间的一致性,以及基于Vcap预测的CONC值与实际测量的CONC值之间的一致性。

结果

在持续输注丙泊酚30分钟后,为每只比格犬选择一个稳定的呼吸周期进行分析。比格犬A计算得出的V/V值为0.535,比格犬B为0.544,比格犬C为0.552。此外,基于CONC和CONC计算得出的V/V值分别为0.494、0.504和0.513。ICC为0.994(P = 0.003),Pearson相关系数r为0.995(P = 0.045),表明两种方法之间具有高度一致性。此外,混合呼出气体预测的CONC值(比格犬A为5.11体积十亿分比(ppbv),比格犬B为5.93 ppbv,比格犬C为2.56 ppbv)与实际CONC值高度一致,ICC为0.996(P = 0.002),Pearson相关系数r为0.994(P = 0.046)。

结论

使用麻醉机现有的时间-容积和时间-CO曲线可以准确测量比格犬混合气体中生理死腔与潮气量的比值,从而校正混合气体样本中呼出丙泊酚的浓度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/046a63f5fa41/12917_2024_4458_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/3e0a93185a6d/12917_2024_4458_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/7e7c2458e98e/12917_2024_4458_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/305256f6f13e/12917_2024_4458_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/bd7d19993ba6/12917_2024_4458_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/046a63f5fa41/12917_2024_4458_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/3e0a93185a6d/12917_2024_4458_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/7e7c2458e98e/12917_2024_4458_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/305256f6f13e/12917_2024_4458_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/bd7d19993ba6/12917_2024_4458_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2693/11706130/046a63f5fa41/12917_2024_4458_Fig5_HTML.jpg

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