He Huaiwu, Chi Yi, Long Yun, Yuan Siyi, Zhang Rui, Yang Yingying, Frerichs Inéz, Möller Knut, Fu Feng, Zhao Zhanqi
Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Department of Anesthesiology and Intensive Care Medicine, University Medical Center of Schleswig-Holstein Campus Kiel, Kiel, Germany.
Ann Intensive Care. 2021 Aug 28;11(1):134. doi: 10.1186/s13613-021-00921-6.
The aim of this study was to validate whether regional ventilation and perfusion data measured by electrical impedance tomography (EIT) with saline bolus could discriminate three broad acute respiratory failure (ARF) etiologies.
Perfusion image was generated from EIT-based impedance-time curves caused by 10 ml 10% NaCl injection during a respiratory hold. Ventilation image was captured before the breath holding period under regular mechanical ventilation. DeadSpace, Shunt and VQMatch were calculated based on lung perfusion and ventilation images. Ventilation and perfusion maps were divided into four cross-quadrants (lower left and right, upper left and right). Regional distribution defects of each quadrant were scored as 0 (distribution% ≥ 15%), 1 (15% > distribution% ≥ 10%) and 2 (distribution% < 10%). Data percentile distributions in the control group and clinical simplicity were taken into consideration when defining the scores. Overall defect scores (Defect, Defect and Defect) were the sum of four cross-quadrants of the corresponding images.
A total of 108 ICU patients were prospectively included: 93 with ARF and 15 without as a control. PaO/FiO was significantly correlated with VQMatch (r = 0.324, P = 0.001). Three broad etiologies of ARF were identified based on clinical judgment: pulmonary embolism-related disease (PED, n = 14); diffuse lung involvement disease (DLD, n = 21) and focal lung involvement disease (FLD, n = 58). The PED group had a significantly higher DeadSpace [40(24)% vs. 14(15)%, PED group vs. the rest of the subjects; median(interquartile range); P < 0.0001] and Defect score than the other groups [1(1) vs. 0(1), PED vs. the rest; P < 0.0001]. The DLD group had a significantly lower Defect score than the PED and FLD groups [0(1) vs. 2.5(2) vs. 3(3), DLD vs. PED vs. FLD; P < 0.0001]. The FLD group had a significantly higher Defect score than the other groups [2(2) vs. 0(1), FLD vs. the rest; P < 0.0001]. The area under the receiver operating characteristic (AUC) for using DeadSpace to identify PED was 0.894 in all ARF patients. The AUC for using the Defect score to identify DLD was 0.893. The AUC for using the Defect score to identify FLD was 0.832.
Our study showed that it was feasible to characterize three broad etiologies of ARF with EIT-based regional ventilation and perfusion. Further study is required to validate clinical applicability of this method. Trial registration clinicaltrials, NCT04081142. Registered 9 September 2019-retrospectively registered, https://clinicaltrials.gov/show/NCT04081142 .
本研究的目的是验证通过注射生理盐水的电阻抗断层成像（EIT）测量的局部通气和灌注数据能否区分三种主要的急性呼吸衰竭（ARF）病因。
在屏气期间，通过注射10ml 10%氯化钠产生基于EIT的阻抗-时间曲线，生成灌注图像。在常规机械通气下屏气期前采集通气图像。根据肺灌注和通气图像计算死腔、分流和通气/灌注匹配度。通气和灌注图被分为四个交叉象限（左下、右下、左上和右上）。每个象限的局部分布缺陷评分为0（分布百分比≥15%）、1（15%＞分布百分比≥10%）和2（分布百分比＜10%）。在定义评分时考虑了对照组的数据百分位数分布和临床简易性。总体缺陷评分（缺陷1、缺陷2和缺陷3）是相应图像四个交叉象限的总和。
前瞻性纳入了108例ICU患者：93例ARF患者和15例非ARF患者作为对照。动脉血氧分压/吸入氧分数值（PaO₂/FiO₂）与通气/灌注匹配度显著相关（r = 0.324，P = 0.001）。基于临床判断确定了ARF的三种主要病因：肺栓塞相关疾病（PED，n = 14）；弥漫性肺受累疾病（DLD，n = 21）和局灶性肺受累疾病（FLD，n = 58）。PED组的死腔[40(24)% vs. 14(15)%，PED组与其他受试者；中位数（四分位间距）；P＜0.0001]和缺陷评分显著高于其他组[1(1) vs. 0(1)，PED组与其他组；P＜0.0001]。DLD组的缺陷评分显著低于PED组和FLD组[0(1) vs. 2.5(2) vs. 3(3)，DLD组 vs. PED组 vs. FLD组；P＜0.0001]。FLD组的缺陷评分显著高于其他组[2(2) vs. 0(1)，FLD组与其他组；P＜0.0001]。在所有ARF患者中，使用死腔识别PED的受试者工作特征曲线下面积（AUC）为0.894。使用缺陷评分识别DLD的AUC为0.893。使用缺陷评分识别FLD的AUC为0.832。
我们的研究表明，用基于EIT的局部通气和灌注来表征ARF的三种主要病因是可行的。需要进一步研究来验证该方法的临床适用性。试验注册：ClinicalTrials，NCT04081142。2019年9月9日注册——回顾性注册，https://clinicaltrials.gov/show/NCT04081142
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