谷歌浏览器插件
订阅小程序
在清言上使用

Assessing Passive Leg Raise Test in Pediatric Shock Using Electrical Cardiometry

Critical care medicine(2022)

引用 0|浏览14
暂无评分
摘要
Passive leg raise (PLR) is widely used to incite an autobolus to assess fluid responsiveness in adults; however, there is a paucity of studies exploring its utility in children. Our study aimed to analyze the efficacy of PLR in determining fluid responsiveness in children presenting with shock using electrical cardiometry. Patients in the age group of 0 to 20 years who presented in shock to our children's hospital emergency department were evaluated. Multiple hemodynamic metrics including, heart rate, systolic/diastolic blood pressure, cardiac output (CO), stroke index, stroke volume (SV), flow time corrected (FTC), and left ventricular ejection time (LVET) were recorded using the noninvasive ICON device and compared at baseline and post-PLR. A total of 68 patients had pre- and post-PLR data available for review between June and July 2022. Median age was 7 years (54% male); most common etiology was hypovolemic (67.6%) shock. Following PLR, there was no significant change in most hemodynamic parameters, including SV and CO; however, there was a significant difference in FTC (301 [pre-PLR] vs. 307 [post-PLR], p = 0.016) (ms) and LVET (232 [pre-PLR] vs. 234 [post-PLR], p = 0.014) (ms). A significantly higher proportion of children diagnosed with septic shock demonstrated fluid responsiveness (Delta SV >= 10% from baseline) compared with those with hypovolemic shock (p = 0.036). This study demonstrated no identifiable fluid responsiveness (Delta SV >= 10% from baseline) following PLR; however, a significantly higher proportion of children suffering from septic shock demonstrated fluid responsiveness compared with those with hypovolemic shock. Larger studies are needed to further assess the utility of PLR, as well as other modalities, in determining fluid responsiveness in children.
更多
查看译文
关键词
passive leg raise,fluid responsiveness,hemodynamic monitoring,NICOM,emergency department
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要