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利用近红外光谱传感器技术无创估计急性神经损伤患者颅内压衍生的脑血管反应性：时间序列分析。

Non-Invasive Estimation of Intracranial Pressure-Derived Cerebrovascular Reactivity Using Near-Infrared Spectroscopy Sensor Technology in Acute Neural Injury: A Time-Series Analysis.

机构信息

Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada.

Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0W2, Canada.

出版信息

Sensors (Basel). 2024 Jan 13;24(2):499. doi: 10.3390/s24020499.

DOI:10.3390/s24020499
PMID:38257592
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10818714/
Abstract

The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO)-based indices of CVR which are less invasive and have improved spatial resolution. This study aims to examine and model the relationship between ICP and rSO-based indices of CVR. Through a retrospective cohort study of prospectively collected physiologic data in moderate to severe traumatic brain injury (TBI) patients, linear mixed effects modeling techniques, augmented with time-series analysis, were utilized to evaluate the ability of rSO-based indices of CVR to model ICP-based indices. It was found that rSO-based indices of CVR had a statistically significant linear relationship with ICP-based indices, even when the hierarchical and autocorrelative nature of the data was accounted for. This strengthens the body of literature indicating the validity of rSO-based indices of CVR and potential greatly expands the scope of CVR monitoring.

摘要

目前，脑血管反应性（CVR）的监测依赖于有创的颅内压（ICP）监测，这限制了其应用。人们对近红外光谱局部脑氧饱和度（rSO2）为基础的 CVR 指数的兴趣正在增加，因为这些指数的侵入性更小，空间分辨率也得到了提高。本研究旨在检验和建立 ICP 与 rSO2 为基础的 CVR 指数之间的关系。通过对中度至重度创伤性脑损伤（TBI）患者前瞻性收集的生理数据进行回顾性队列研究，采用线性混合效应模型技术，并结合时间序列分析，评估 rSO2 为基础的 CVR 指数对 ICP 为基础的指数的建模能力。结果发现，即使考虑到数据的层次结构和自相关性，rSO2 为基础的 CVR 指数与 ICP 为基础的指数之间也存在统计学上显著的线性关系。这进一步证实了 rSO2 为基础的 CVR 指数的有效性，并可能极大地扩展了 CVR 监测的范围。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3ab/10818714/c889bb374fe2/sensors-24-00499-g006.jpg
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