医学
冲程容积
置信区间
麻醉
预加载
体积热力学
潮气量
血流动力学
外科
内科学
心率
血压
量子力学
物理
呼吸系统
作者
Xixi Tang,Qi Chen,Zejun Huang,Jingqiu Liang,Ran An,Hongliang Liu
标识
DOI:10.1007/s11701-023-01710-y
摘要
We aimed to compare the ability of carotid corrected flow time assessed by ultrasound and the changes in dynamic preload indices induced by tidal volume challenge predicting fluid responsiveness in patients undergoing robot-assisted laparoscopic gynecological surgery in the modified head-down lithotomy position. This prospective single-center study included patients undergoing robot-assisted laparoscopic surgery in the modified head-down lithotomy position. Carotid Doppler parameters and hemodynamic data, including corrected flow time, pulse pressure variation, stroke volume variation, and stroke volume index at a tidal volume of 6 mL/kg predicted body weight and after increasing the tidal volume to 8 mL/kg predicted body weight (tidal volume challenge), respectively, were measured. Fluid responsiveness was defined as a stroke volume index ≥ 10% increase after volume expansion. Among the 52 patients included, 26 were classified as fluid responders and 26 as non-responders based on the stroke volume index. The area under the receiver operating characteristic curve measured to predict the fluid responsiveness to corrected flow time and changes in pulse pressure variation (ΔPPV6-8) after tidal volume challenge were 0.82 [95% confidence interval (CI) 0.71-0.94; P < 0.0001] and 0.85 (95% CI 0.74-0.96; P < 0.0001), respectively. The value for pulse pressure variation at a tidal volume of 8 mL/kg was 0.79 (95% CI 0.67-0.91; P = 0.0003). The optimal cut-off values for corrected flow time and ΔPPV6-8 were 357 ms and > 1%, respectively. Both the corrected flow time and Changes in pulse pressure variation after tidal volume challenge reliably predicted fluid responsiveness in patients undergoing robot-assisted laparoscopic gynecological surgery in the modified head-down lithotomy position. And pulse pressure variation at a tidal volume of 8 mL/kg maybe also a useful predictor.Trial registration: Chinese Clinical Trial Register (CHiCTR2200060573, Principal investigator: Hongliang Liu, Date of registration: 05/06/2022).
科研通智能强力驱动
Strongly Powered by AbleSci AI