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Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

机译:颅内病理物理学选定相关分析的参数优化

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Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.
机译:最近我们提出了一种称为所选相关性分析的数学工具集,可靠地检测动脉血压(ABP)和颅内压(ICP)之间的正相关和负相关。这种相关性与脑自动调节和颅内遵从的严重损害相关,如数学模型所预测的。解决了所选相关性分析的时间基于窗口技术与傅立叶的相干计算结合,因此取决于若干参数。为了在ICU上实时应用此方法,它不可避免地调整该数学工具以获得高灵敏度和不同的可靠性。在本研究中,我们将通过将被称为所选相关性正(SCP)的指数相关联,介绍一种方法来优化所选择的相关分析的参数,其中包括Glasgow结果规模(GOS)所代表的患者的结果。为此目的,二十五名患者的数据用于计算所选择的相关分析的每位患者的SCP值和众多可行的参数集。可以说明,与我们的第一次分析相比,优化的一组参数能够将方法的灵敏度提高到大于四个超过四个。

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