• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Novel incorporation of biomedical engineering algorithms (bispectral index guided or anesthetic concentration guided) in real-time decision support to prevent intraoperative awareness using an electronic anesthesia information management system.
【24h】

Novel incorporation of biomedical engineering algorithms (bispectral index guided or anesthetic concentration guided) in real-time decision support to prevent intraoperative awareness using an electronic anesthesia information management system.

机译：实时决策支持中将生物医学工程算法（双频谱指数指导或麻醉药浓度指导）进行了新的合并，以防止使用电子麻醉信息管理系统进行术中知晓。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Background: Intraoperative awareness with explicit recall (AWR) is a feared complication of surgery that can lead to significant psychological distress. Several large prospective trials have been completed comparing two methods of monitoring anesthetic depth [minimum alveolar concentration (MAC) or electroencephalography (EEG) monitoring using the bispectral index (BIS)] for the prevention of AWR. However, these trials were conducted in high risk populations, limiting generalizability.;Research Hypothesis: Real-time decision support with Anesthesia Information Management System alerts based on a novel anesthetic concentration algorithm (incorporating the use of intravenous anesthetics) or an EEG-guided algorithm will reduce the known incidence of AWR.;Methods: First, a MAC-equivalent alerting algorithm that incorporates the use of intravenous anesthetics was developed and retrospectively applied to previously collected data. A threshold was calculated that demonstrated optimal sensitivity and specificity for detecting AWR. Next, a large prospective randomized controlled trial was performed in an unselected surgical population to compare the MAC-equivalent or a BIS alerting algorithm for the prevention of AWR. Finally, discrete intraoperative data collected during that trial were analyzed to determine which specific threshold for MAC or BIS demonstrated optimal sensitivity and specificity in the eradication of AWR.;Results: Retrospective analysis revealed that a MAC-equivalent of <0.5 was associated with the highest positive likelihood ratio; this was used as the threshold in the prospective trial. No difference was detected between BIS or MAC-equivalent alerting algorithms in the reduction of AWR. Post hoc analysis revealed that BIS, when compared to routine clinical care without alerts, demonstrated a 4.7 fold reduction in definite or possible AWR. By secondary analysis, neither MAC nor BIS demonstrated a discrete population-based threshold with optimal sensitivity and specificity in the prevention of AWR.;Conclusion: No difference was detected in the reduction of AWR between BIS or MAC alerting. However, BIS alerting when compared to standard of care reduced the incidence of AWR. There were no discriminating thresholds of MAC or BIS values at the population level associated with the eradication of AWR. In conclusion, real-time decision support reduces the incidence of AWR but individualized patient-based alerting algorithms will be required for its eradication.
机译：背景：术中有明确回忆的意识（AWR）是一种令人恐惧的手术并发症，可能导致严重的心理困扰。已经完成了一些大型前瞻性试验，比较了两种监测麻醉深度的方法[使用双光谱指数（BIS）监测最低肺泡浓度（MAC）或脑电图（EEG）]预防AWR。但是，这些试验是在高风险人群中进行的，这限制了推广的可能性。研究假设：基于新型麻醉剂浓度算法（结合使用静脉麻醉剂）或EEG指导的麻醉信息管理系统警报的实时决策支持方法：首先，开发了一种MAC等效警报算法，该算法结合了静脉麻醉药的使用，并将其追溯应用于先前收集的数据。计算的阈值显示出检测AWR的最佳灵敏度和特异性。接下来，在未选择的手术人群中进行了一项大型前瞻性随机对照试验，以比较MAC等效法或BIS预警算法对预防AWR的影响。最后，分析了该试验期间收集的离散术中数据，以确定MAC或BIS的哪个特定阈值显示出根除AWR的最佳敏感性和特异性。结果：回顾性分析显示，MAC等效值<0.5与最高正似然比；这被用作前瞻性试验的门槛。在减少AWR方面，在BIS或等效于MAC的警报算法之间未检测到差异。事后分析显示，与无预警的常规临床护理相比，BIS的确定或可能的AWR降低了4.7倍。通过二级分析，MAC和BIS均未显示出基于人群的离散阈值，具有最佳的敏感性和特异性，可预防AWR。结论：在BIS或MAC警报之间，AWR的降低没有发现差异。然而，与护理标准相比，BIS警报降低了AWR的发生率。在消除AWR的人群中，没有MAC或BIS值的判别阈值。总之，实时决策支持可以减少AWR的发生，但是根除AWR需要基于患者的个性化警报算法。

著录项

  • 作者

    Shanks, Amy Melanie.;

  • 作者单位

    Wayne State University.;

  • 授予单位 Wayne State University.;
  • 学科 Health care management.;Biomedical engineering.;Information technology.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 212 p.
  • 总页数 212
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号