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外周动脉峰值速度的变异性可预测感染性休克患者的液体反应性

[Variability of peripheral arterial peak velocity predicts fluid responsiveness in patients with septic shock].

作者信息

Lu Nianfang, Jiang Li, Zhu Bo, Han Wenyong, Zhao Yingqi, Shi Yuntao, Guo Fashuang, Xi Xiuming

机构信息

Department of Intensive Care Unit, Beijing Electric Power Hospital, National Electric Net Ltd., Beijing 100073, China (Lu NF, Zhao YQ, Shi YT, Guo FS); Department of Anesthesiology, Beijing Electric Power Hospital, National Electric Net Ltd., Beijing 100073, China (Han WY); Department of Intensive Care Unit, Beijing Fuxing Hospital, Capital Medical University, Beijing 100038, China (Jiang L, Zhu B, Xi Xiuming). Corresponding author: Xi Xiuming, Email:

出版信息

Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2018 Mar;30(3):224-229. doi: 10.3760/cma.j.issn.2095-4352.2018.03.007.

Abstract

OBJECTIVE

To explore the accuracy of fluid responsiveness assessment by variability of peripheral arterial peak velocity and variability of inferior vena cava diameter (ΔIVC) in patients with septic shock.

METHODS

A prospective study was conducted. The patients with septic shock undergoing mechanical ventilation (MV) admitted to intensive care unit (ICU) of Beijing Electric Power Hospital from January 2016 to December 2017 were enrolled. According to sepsis bundles of septic shock, volume expansion (VE) was conducted. The increase in cardiac index (ΔCI) after VE ≥ 10% was defined as liquid reaction positive (responsive group), ΔCI < 10% was defined as the liquid reaction negative (non-responsive group). The hemodynamic parameters [central venous pressure (CVP), intrathoracic blood volume index (ITBVI), stroke volume variation (SVV), ΔIVC, variability of carotid Doppler peak velocity (ΔCDPV), and variability of brachial artery peak velocity (ΔVpeak-BA)] before and after VE were monitored. The correlations between the hemodynamic parameters and ΔCI were explored by Pearson correlation analysis. Receiver operating characteristic (ROC) curve was plotted to analyze the predictive value of all hemodynamic parameters on fluid responsiveness.

RESULTS

During the study, 74 patients with septic shock were included, of whom 9 were excluded because of peripheral artery stenosis, recurrent arrhythmia or abdominal distension influencing the ultrasound examination, and 65 patients were finally enrolled in the analysis. There were 31 patients in the responsive group and 34 in the non-responsive group. SVV, ΔIVC, ΔCDPV and ΔVpeak-BA before VE in responsive group were significantly higher than those of the non-responsive group [SVV: (12.3±2.4)% vs. (9.2±2.1)%, ΔIVC: (22.3±5.3)% vs. (15.5±3.7)%, ΔCDPV: (15.3±3.3)% vs. (10.3±2.4)%, ΔVpeak-BA: (14.5±3.3)% vs. (9.6±2.3)%, all P < 0.05]. There was no significant difference in CVP [mmHg (1 mmHg = 0.133 kPa): 7.5±2.5 vs. 8.2±2.6] or ITBVI (mL/m: 875.2±173.2 vs. 853.2±192.0) between the responsive group and non-responsive group (both P > 0.05). There was no significant difference in hemodynamic parameter after VE between the two groups. Correlation analysis showed that SVV, ΔIVC, ΔCDPV, and ΔVpeak-BA before VE showed significant linearity correlation with ΔCI (r value was 0.832, 0.813, 0.854, and 0.814, respectively, all P < 0.05), but no correlation was found between CVP and ΔCI (r = -0.342, P > 0.05) as well as ITBVI and ΔCI (r = -0.338, P > 0.05). ROC curve analysis showed that the area under ROC curve (AUC) of SVV, ΔIVC, ΔCDPV, and ΔVpeak-BA before VE for predicting fluid responsiveness was 0.857, 0.826, 0.906, and 0.866, respectively, which was significantly higher than that of CVP (AUC = 0.611) and ITBVI (AUC = 0.679). When the optimal cut-off value of SVV for predicting fluid responsiveness was 11.5%, the sensitivity was 70.4%, and the specificity was 94.7%. When the optimal cut-off value of ΔIVC was 20.5%, the sensitivity was 60.3%, and the specificity was 89.7%. When the optimal cut-off value of ΔCDPV was 13.0%, the sensitivity was 75.2%, and the specificity was 94.9%. When the optimal cut-off value of ΔVpeak-BA was 12.7%, the sensitivity was 64.8%, and the specificity was 89.7%.

CONCLUSIONS

Ultrasound assessment of ΔIVC, ΔCDPV, and ΔVpeak-BA could predict fluid responsiveness in patients with septic shock receiving mechanical ventilation. ΔCDPV had the highest predictive value among these parameters.

摘要

目的

探讨外周动脉峰值速度变异性和下腔静脉直径变异(ΔIVC)对感染性休克患者液体反应性评估的准确性。

方法

进行一项前瞻性研究。纳入2016年1月至2017年12月在北京电力医院重症监护病房(ICU)接受机械通气(MV)的感染性休克患者。根据感染性休克的集束化治疗方案进行容量扩充(VE)。VE后心脏指数增加(ΔCI)≥10%定义为液体反应阳性(反应组),ΔCI<10%定义为液体反应阴性(无反应组)。监测VE前后的血流动力学参数[中心静脉压(CVP)、胸腔内血容量指数(ITBVI)、每搏量变异(SVV)、ΔIVC、颈动脉多普勒峰值速度变异(ΔCDPV)和肱动脉峰值速度变异(ΔVpeak-BA)]。通过Pearson相关分析探讨血流动力学参数与ΔCI之间的相关性。绘制受试者工作特征(ROC)曲线分析所有血流动力学参数对液体反应性的预测价值。

结果

研究期间,纳入74例感染性休克患者,其中9例因外周动脉狭窄、反复心律失常或腹胀影响超声检查而被排除,最终65例患者纳入分析。反应组31例,无反应组34例。反应组VE前的SVV、ΔIVC、ΔCDPV和ΔVpeak-BA显著高于无反应组[SVV:(12.3±2.4)%对(9.2±2.1)%,ΔIVC:(22.3±5.3)%对(15.5±3.7)%,ΔCDPV:(15.3±3.3)%对(10.3±2.4)%,ΔVpeak-BA:(14.5±3.3)%对(9.6±2.3)%,均P<0.05]。反应组与无反应组之间的CVP[mmHg(1 mmHg = 0.133 kPa):7.5±2.5对8.2±2.6]或ITBVI(mL/m:875.2±173.2对853.2±192.0)无显著差异(均P>0.05)。两组VE后的血流动力学参数无显著差异。相关分析显示,VE前的SVV、ΔIVC、ΔCDPV和ΔVpeak-BA与ΔCI呈显著线性相关(r值分别为0.832、0.813、0.854和0.814,均P<0.05),但CVP与ΔCI(r = -0.342,P>0.05)以及ITBVI与ΔCI(r = -0.338,P>0.05)之间无相关性。ROC曲线分析显示,VE前SVV、ΔIVC、ΔCDPV和ΔVpeak-BA预测液体反应性的ROC曲线下面积(AUC)分别为0.857、0.826、0.906和0.866,显著高于CVP(AUC = 0.611)和ITBVI(AUC = 0.679)。当预测液体反应性的SVV最佳截断值为11.5%时,敏感性为70.4%,特异性为94.7%。当ΔIVC的最佳截断值为20.5%时,敏感性为60.3%,特异性为89.7%。当ΔCDPV的最佳截断值为13.0%时,敏感性为75.2%,特异性为94.9%。当ΔVpeak-BA的最佳截断值为12.7%时,敏感性为64.8%,特异性为89.7%。

结论

超声评估ΔIVC、ΔCDPV和ΔVpeak-BA可预测接受机械通气的感染性休克患者的液体反应性。这些参数中ΔCDPV的预测价值最高。

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