Pitfalls and possibilities of using Root SedLine for continuous assessment of EEG waveform-based metrics in intensive care research.

IF 2.3 4区 医学 Q3 BIOPHYSICS
Stefan Yu Bögli, Marina Sandra Cherchi, Ihsane Olakorede, Andrea Lavinio, Erta Beqiri, Ethan Moyer, Dick Moberg, Peter Smielewski
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Abstract

Objective.The Root SedLine device is used for continuous electroencephalography (cEEG)-based sedation monitoring in intensive care patients. The cEEG traces can be collected for further processing and calculation of relevant metrics not already provided. Depending on the device settings during acquisition, the acquired traces may be distorted by max/min value cropping or high digitization errors. We aimed to systematically assess the impact of these distortions on metrics used for clinical research in the field of neuromonitoring.Approach.A 16 h cEEG acquired using the Root SedLine device at the optimal screen settings was analyzed. Cropping and digitization error effects were simulated by consecutive reduction of the maximum cEEG amplitude by 2µV or by reducing the vertical resolution. Metrics were calculated within ICM+ using minute-by-minute data, including the total power, alpha delta ratio (ADR), and 95% spectral edge frequency. Data were analyzed by creating violin- or box-plots.Main Results.Cropping led to a continuous reduction in total and band power, leading to corresponding changes in variability thereof. The relative power and ADR were less affected. Changes in resolution led to relevant changes. While the total power and power of low frequencies were rather stable, the power of higher frequencies increased with reducing resolution.Significance.Care must be taken when acquiring and analyzing cEEG waveforms from Root SedLine for clinical research. To retrieve good quality metrics, the screen settings must be kept within the central vertical scale, while pre-processing techniques must be applied to exclude unacceptable periods.

在重症监护研究中使用 Root SedLine 对基于脑电图波形的指标进行连续评估的隐患和可能性。
目标:Root SedLine 设备用于对重症监护患者进行基于连续脑电图(cEEG)的镇静监测。采集的 cEEG 曲线可用于进一步处理和计算尚未提供的相关指标。根据采集时的设备设置,采集到的轨迹可能会因最大/最小值裁剪或数字化误差过大而失真。我们旨在系统地评估这些失真对神经监测领域临床研究指标的影响:我们对使用 Root SedLine 设备在最佳屏幕设置下采集的 16 小时 cEEG 进行了分析。通过将最大 cEEG 振幅连续降低 2µV 或降低垂直分辨率来模拟裁剪和数字化误差的影响。在 ICM+ 中使用逐分钟数据计算指标,包括总功率、α δ 比值和 95% 光谱边缘频率。通过创建小提琴图或箱形图对数据进行分析:裁剪导致总功率和频带功率持续下降,从而导致其变异性发生相应变化。相对功率和阿尔法δ比值受到的影响较小。分辨率的变化导致了相关的变化。总功率和低频功率相当稳定,而高频功率则随着分辨率的降低而增加:在临床研究中获取和分析 Root SedLine 的 cEEG 波形时必须小心谨慎。为了获得高质量的指标,屏幕设置必须保持在中央垂直刻度范围内,同时必须应用预处理技术排除不可接受的时段。
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来源期刊
Physiological measurement
Physiological measurement 生物-工程:生物医学
CiteScore
5.50
自引率
9.40%
发文量
124
审稿时长
3 months
期刊介绍: Physiological Measurement publishes papers about the quantitative assessment and visualization of physiological function in clinical research and practice, with an emphasis on the development of new methods of measurement and their validation. Papers are published on topics including: applied physiology in illness and health electrical bioimpedance, optical and acoustic measurement techniques advanced methods of time series and other data analysis biomedical and clinical engineering in-patient and ambulatory monitoring point-of-care technologies novel clinical measurements of cardiovascular, neurological, and musculoskeletal systems. measurements in molecular, cellular and organ physiology and electrophysiology physiological modeling and simulation novel biomedical sensors, instruments, devices and systems measurement standards and guidelines.
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