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通过绵羊模型中的无创参数提高通气期间 PaCO2 对呼气末 CO2 的估计。

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

机构信息

Department of Paediatric and Adolescent Medicine, RWTH Aachen University Hospital, Aachen, Germany.

Embedded Software - Informatik 11, RWTH Aachen University, Aachen, Germany.

出版信息

Biomed Eng Online. 2024 Oct 24;23(1):104. doi: 10.1186/s12938-024-01292-2.

Abstract

BACKGROUND

In mechanically ventilated neonates, the arterial partial pressure of ( ) is an important indicator for the adequacy of ventilation settings. Determining the 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 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 in neonates on the basis of end-tidal ( ) with inclusion of different physiological and ventilation parameters. The estimation method should be more accurate than an estimation by unaltered 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 measurements below or equal to 75 mmHg from the first day of life. 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 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 by blood gas analysis.

CONCLUSIONS

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

摘要

背景

在机械通气的新生儿中,动脉血二氧化碳分压( )是评估通气设置是否充分的重要指标。通常通过有创血气分析来确定 ,但这对新生儿存在风险,且通常只能偶尔进行。对于医务人员来说,准确、可靠、连续地估计 非常重要,这使得他们能够更密切地监测并对变化做出更快的反应。我们旨在提出一种基于潮气末二氧化碳( )的无创新生儿 估计方法,其中包括不同的生理和通气参数。与未经修正的 测量相比,该估计方法在均方误差和标准差方面应更准确。

方法

使用 51 只早产羔羊的二级数据,因为其与早产儿数据具有高度可比性。我们利用稳健线性回归对出生后第一天至第 75 天以下的 863 次 测量值进行分析。回归中包含 以及一组通气设置和测量值以及生命参数。选择的独立变量是通过与剩余估计偏差的最高皮尔逊相关性迭代确定的。

结果

在出生后前两天的 12 只新生羔羊中进行了 246 次 75mmHg 以下的测量,对该估计方法进行了评估。与血气分析测量的 相比,该估计方法的平均绝对误差为 3.80mmHg,差异的 4.92mmHg 标准差和 0.31mmHg 的标准误差。

结论

与未经修正的 相比,提出的方程估计 偏差更小。该方法在临床实践中的应用或在通气自动化等应用中的使用需要进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f474/11515479/cfca7201b87f/12938_2024_1292_Fig1_HTML.jpg

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