An evaluation of remifentanil propofol response surfaces for loss of responsiveness, loss of response to surrogates of painful stimuli and laryngoscopy in patients undergoing elective surgery

对择期手术患者使用瑞芬太尼丙泊酚进行反应面评估,包括反应丧失、对疼痛刺激替代物的反应丧失以及喉镜检查。

阅读:1

Abstract

INTRODUCTION: In this study, we explored how a set of remifentanil-propofol response surface interaction models developed from data collected in volunteers would predict responses to events in patients undergoing elective surgery. Our hypotheses were that these models would predict a patient population's loss and return of responsiveness and the presence or absence of a response to laryngoscopy and the response to pain after surgery. METHODS: Twenty-one patients were enrolled. Anesthesia consisted of remifentanil and propofol infusions and fentanyl boluses. Loss and return of responsiveness, responses to laryngoscopy, and responses to postoperative pain were assessed in each patient. Model predictions were compared with observed responses. RESULTS: The loss of responsiveness model predicted that patients would become unresponsive 2.4 +/- 2.6 min earlier than observed. At the time of laryngoscopy, the laryngoscopy model predicted an 89% probability of no response to laryngoscopy and 81% did not respond. During emergence, the loss of responsiveness model predicted return of responsiveness 0.6 +/- 5.1 min before responsiveness was observed. The mean probability of no response to pressure algometry was 23% +/- 35% when patients required fentanyl for pain control. DISCUSSION: This preliminary assessment of a series of remifentanil-propofol interaction models demonstrated that these models predicted responses to selected pertinent events during elective surgery. However, significant model error was evident during rapid changes in predicted effect-site propofol-remifentanil concentration pairs.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。