Sun Xiu-Mei, Chen Guang-Qiang, Chen Kai, Wang Yu-Mei, He Xuan, Huang Hua-Wei, Luo Xu-Ying, Wang Chun-Mei, Shi Zhong-Hua, Xu Ming, Chen Lu, Fan Eddy, Zhou Jian-Xin
Department of Critical Care Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Keenan Research Centre, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.
Respir Care. 2018 Sep;63(9):1094-1101. doi: 10.4187/respcare.06151. Epub 2018 Jun 26.
Stress index provides a noninvasive approach to detect injurious ventilation patterns and to personalize ventilator settings. Obtaining the stress index (SI), however, requires quantitatively analyzing the shape of pressure-time curve with dedicated instruments or a specific ventilator, which may encumber its clinical implementation. We hypothesized that the SI could be qualitatively determined through a visual inspection of ventilator waveforms.
Thirty-six adult subjects undergoing volume controlled ventilation without spontaneous breathing were enrolled. For each subject, 2 trained clinicians visually inspected the pressure-time curve directly from the ventilator screen. They then qualitatively categorized the shape of pressure-time curve as linear, a downward concavity, or an upward concavity at the bedside. We simultaneously recorded airway pressure and flow signals using a dedicated instrument. A quantitative off-line analysis was performed to calculate the SI using specific research software. This quantitative analysis of the SI served as the reference method for classifying the shape of the pressure-time curve (ie, linear, a downward concavity, or an upward concavity). We compared the SI categorized by visual inspection with that by the reference.
We obtained 200 SI assessments of pressure-time curves, among which 125 (63%) were linear, 55 (27%) were a downward concavity, and 20 (10%) were an upward concavity as determined by the reference method. The overall accuracy of visual inspection and weighted kappa statistic (95% CI) was 93% (88-96%) and 0.88 (0.82-0.94), respectively. The sensitivity and specificity to distinguish a downward concavity from a linear shape were 91% and 98%, respectively. The respective sensitivity and specificity to distinguish an upward concavity from a linear shape were 95% and 95%.
Visual inspection of the pressure-time curve on the ventilator screen is a simple and reliable approach to assess SI at the bedside. This simplification may facilitate the implementation of SI in clinical practice to personalize mechanical ventilation. (ClinicalTrials.gov registration NCT03096106.).
压力指数提供了一种非侵入性方法，用于检测有害的通气模式并使呼吸机设置个性化。然而，获取压力指数（SI）需要使用专用仪器或特定呼吸机对压力 - 时间曲线的形状进行定量分析，这可能会阻碍其临床应用。我们假设可以通过目视检查呼吸机波形来定性确定SI。
招募了36名接受无自主呼吸的容量控制通气的成年受试者。对于每个受试者，2名经过培训的临床医生直接从呼吸机屏幕上目视检查压力 - 时间曲线。然后他们在床边将压力 - 时间曲线的形状定性分类为线性、向下凹陷或向上凹陷。我们使用专用仪器同时记录气道压力和流量信号。使用特定的研究软件进行定量离线分析以计算SI。SI的这种定量分析用作对压力 - 时间曲线形状（即线性、向下凹陷或向上凹陷）进行分类的参考方法。我们将目视检查分类的SI与参考分类的SI进行比较。
我们获得了200次压力 - 时间曲线的SI评估，其中参考方法确定125次（63％）为线性，55次（27％）为向下凹陷，20次（10％）为向上凹陷。目视检查的总体准确率和加权kappa统计量（95％CI）分别为93％（88 - 96％）和0.88（0.82 - 0.94）。区分向下凹陷与线性形状的敏感性和特异性分别为91％和98％。区分向上凹陷与线性形状的相应敏感性和特异性分别为95％和95％。
在呼吸机屏幕上目视检查压力 - 时间曲线是一种在床边评估SI的简单可靠方法。这种简化可能有助于SI在临床实践中的应用，以使机械通气个性化。（ClinicalTrials.gov注册号NCT03096106。）
