Enhancing the estimation of PaCO2 from etCO2 during ventilation through non-invasive parameters in the ovine model.

IF 2.9 4区 医学 Q3 ENGINEERING, BIOMEDICAL
Mike Grüne, Lena Olivier, Valerie Pfannschmidt, Matthias Hütten, Thorsten Orlikowsky, Andre Stollenwerk, Mark Schoberer
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引用次数: 0

Abstract

Background: In mechanically ventilated neonates, the arterial partial pressure of CO 2 ( PaCO 2 ) is an important indicator for the adequacy of ventilation settings. Determining the PaCO 2 is commonly done using invasive blood gas analyses, which constitute risks for neonates and are typically only available infrequently. An accurate, reliable, and continuous estimation of PaCO 2 is of high interest for medical staff, giving the possibility of a closer monitoring and faster reactions to changes. We aim to present a non-invasive estimation method for PaCO 2 in neonates on the basis of end-tidal CO 2 ( etCO 2 ) with inclusion of different physiological and ventilation parameters. The estimation method should be more accurate than an estimation by unaltered etCO 2 measurements with regard to the mean absolute error and the standard deviation.

Methods: Secondary data from 51 preterm lambs are used, due to its high comparability to preterm human data. We utilize robust linear regression on 863 PaCO 2 measurements below or equal to 75 mmHg from the first day of life. etCO 2 along with a set of ventilation settings and measurements as well as vital parameters are included in the regression. Included independent variables are chosen iteratively by highest Pearson correlation to the remaining estimation deviation.

Results: The evaluation is carried out on 12 additional neonatal lambs with 246 PaCO 2 measurements below or equal to 75 mmHg from the first two days of life. The estimation method shows a mean absolute error of 3.80 mmHg with a 4.92 mmHg standard deviation of differences and a standard error of 0.31 mmHg in comparison to measured PaCO 2 by blood gas analysis.

Conclusions: The estimation of PaCO 2 by the proposed equation is less biased than unaltered etCO 2 . The usage of this method in clinical practice or in applications like the automation of ventilation needs further investigation.

在绵羊模型中,通过非侵入性参数加强通气过程中根据 etCO2 估算 PaCO2。
背景:在机械通气的新生儿中,动脉二氧化碳分压(PaCO 2)是衡量通气设置是否充分的重要指标。确定 PaCO 2 通常采用有创血气分析法,但这种方法对新生儿有风险,而且通常不常使用。准确、可靠、持续地估算 PaCO 2 值是医务人员非常关心的问题,这样可以更密切地监测病情变化并做出更快的反应。我们的目标是在潮气末 CO 2 ( etCO 2 ) 的基础上,结合不同的生理和通气参数,提出一种无创的新生儿 PaCO 2 估算方法。就平均绝对误差和标准偏差而言,该估算方法应比未经改变的 etCO 2 测量值估算更为准确:方法:我们使用了 51 只早产羔羊的二手数据,因为这些数据与人类早产羔羊的数据具有很高的可比性。我们利用稳健线性回归法对出生第一天起低于或等于 75 mmHg 的 863 个 PaCO 2 测量值进行回归。根据与剩余估计偏差的最高皮尔逊相关性反复选择所包含的自变量:对另外 12 只新生羔羊进行了评估,这些羔羊在出生后头两天内有 246 次 PaCO 2 测量值低于或等于 75 mmHg。与通过血气分析测得的 PaCO 2 相比,该估算方法的平均绝对误差为 3.80 mmHg,差异标准偏差为 4.92 mmHg,标准误差为 0.31 mmHg:结论:与未经改变的等CO 2 相比,用提出的等式估计 PaCO 2 的偏差较小。这种方法在临床实践或通气自动化等应用中的使用还需进一步研究。
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来源期刊
BioMedical Engineering OnLine
BioMedical Engineering OnLine 工程技术-工程:生物医学
CiteScore
6.70
自引率
2.60%
发文量
79
审稿时长
1 months
期刊介绍: BioMedical Engineering OnLine is an open access, peer-reviewed journal that is dedicated to publishing research in all areas of biomedical engineering. BioMedical Engineering OnLine is aimed at readers and authors throughout the world, with an interest in using tools of the physical and data sciences and techniques in engineering to understand and solve problems in the biological and medical sciences. Topical areas include, but are not limited to: Bioinformatics- Bioinstrumentation- Biomechanics- Biomedical Devices & Instrumentation- Biomedical Signal Processing- Healthcare Information Systems- Human Dynamics- Neural Engineering- Rehabilitation Engineering- Biomaterials- Biomedical Imaging & Image Processing- BioMEMS and On-Chip Devices- Bio-Micro/Nano Technologies- Biomolecular Engineering- Biosensors- Cardiovascular Systems Engineering- Cellular Engineering- Clinical Engineering- Computational Biology- Drug Delivery Technologies- Modeling Methodologies- Nanomaterials and Nanotechnology in Biomedicine- Respiratory Systems Engineering- Robotics in Medicine- Systems and Synthetic Biology- Systems Biology- Telemedicine/Smartphone Applications in Medicine- Therapeutic Systems, Devices and Technologies- Tissue Engineering
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