west china medical publishers
Author
  • Title
  • Author
  • Keyword
  • Abstract
Advance search
Advance search

Search

find Author "QIAN Yajun" 1 results
  • Clinical study on the predictive value of dynamic energy expenditure monitoring to guide the weaning from mechanical ventilation

    ObjectiveTo compare the predictive values of dynamic energy expenditure (EE) monitoring and the traditional method (rapid shallow breath index) for weaning in patient who is suitable for weaning from mechanical ventilation and accepts sequentially reduced support of ventilator.MethodsThis study included a total of 93 patients who were admitted to the Department of Intensive Care Medicine in 2018 to 2019, and were eligible for weaning from mechanical ventilation. The energy expenditure monitoring device of GE ventilator (CARESCAPE R860) was used to record the patient's change rate of EE [δEE(%), T1 (PSV 20/5), T2 (PSV 15/5), T3 (PSV 10-5/5), T4 (PSV 5/5)] while the ventilation support was declined. The differences in δEE were compared between the two groups of patients who were successful weaned (a successful group S) or failed (a failed group) at different phases. The receiver operator characteristic (ROC) curve was used to analyze the predictive value of δEE to the success rate of weaning.ResultA total of 36 patients failed weaning procedure. There was no significant difference in the basic status and disease type between the successful group and the failed group. There was no difference in δEE1 between T1-T2 phases [(5.67±2.31)% vs. (6.40±1.90)%, P>0.05], but significant difference in δEE between T2-T3 and T3-T4 phases [δEE2: (11.35±5.39)% vs. (14.21±6.33)%, P<0.05; δEE3: (8.39±3.90)% vs. (17.32±9.07)%, P<0.05]. The area under the ROC curve predicted by δEE2 and δEE3 for the patient's weaning results was higher than rapid shallow breath index (0.83 and 0.75 vs. 0.64, P<0.05).ConclusionDynamic energy expenditure monitoring can effectively evaluate and predict the success rate of weaning from mechanical ventilation, and can be applied to the clinical treatment process.

    Release date:2021-06-30 03:37 Export PDF Favorites Scan
1 pages Previous 1 Next

Format

Content