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使用咪达唑仑和阿片类药物的胃肠内镜检查给药策略的响应面模型探索

A Response Surface Model Exploration of Dosing Strategies in Gastrointestinal Endoscopies Using Midazolam and Opioids.

作者信息

Liou Jing-Yang, Ting Chien-Kun, Hou Ming-Chih, Tsou Mei-Yung

机构信息

From the Department of Anesthesiology, Taipei Veterans General Hospital (J-YL, C-KT, M-YT), National Yang-Ming University and School of Medicine (C-KT, M-CH, M-YT), and Center for Diagnostic and Treatment Endoscopy, Taipei Veterans General Hospital, Taipei, Taiwan, ROC (M-CH).

出版信息

Medicine (Baltimore). 2016 Jun;95(23):e3520. doi: 10.1097/MD.0000000000003520.

DOI:10.1097/MD.0000000000003520
PMID:27281065
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4907643/
Abstract

Classical midazolam-opioid combination for gastrointestinal endoscopy sedation has been adopted for decades. Dosing regimens have been studied but most require fixed dosing intervals. We intend to use a sophisticated pharmacodynamic tool, response surface model (RSM), to simulate sedation using different regimens. RSM can predict patient's response during different phases of the examination and predict patient's wake-up time with precision and without the need for fixed dosing intervals. We believe it will aid physicians in guiding their dosing strategy and timing.The study is divided into 2 parts. The first part is the full Greco RSMs development for 3 distinct phases: esophagogastroduodenoscopy (EGD), colonoscopy, and intersession (the time lapse between procedures). Observer's Assessment of Alertness Score (OAA/S) is used to assess patient response. The second part simulates 6 regimens with different characteristics using the RSMs: midazolam only, balanced midazolam and opioids, high-dose opioids and midazolam, low-dose midazolam with high-dose opioids, high-dose midazolam and low-dose opioids, and finally midazolam with continuous opioid infusion. Loss of response at 95% probability for adequate anesthesia during examination and return of consciousness at 50% probability during intersession was selected for simulation purposes.The average age of the patient population is 49.3 years. Mean BMI is 21.9 ± 2.3 kg/m. About 56.7% were females and none received prior abdominal surgery. The cecal intubation rate was 100%. Only 1 patient (3%) developed temporary hypoxemia, which was promptly managed with simple measures. The RSMs for each phase showed significant synergy between midazolam and alfentanil. The balanced midazolam and alfentanil combination provided adequate anesthesia and most rapid return of consciousness. The awakening time from the final drug bolus was 7.4 minutes during EGD and colonoscopy stimulation, and 9.1 minutes during EGD simulation.Simulation of regimens with different characteristics gives insights on dosing strategies. A balanced midazolam-alfentanil regimen is adequate in providing good anesthetic depth and most rapid return of consciousness. We believe with the aid of our RSM, clinicians can perform sedation with more flexibility and precision.

摘要

经典的咪达唑仑 - 阿片类药物联合用于胃肠内镜检查镇静已被采用数十年。已经对给药方案进行了研究,但大多数方案需要固定的给药间隔。我们打算使用一种复杂的药效学工具——响应面模型(RSM),来模拟不同给药方案下的镇静情况。RSM可以预测患者在检查不同阶段的反应,并精确预测患者的苏醒时间,且无需固定给药间隔。我们相信它将有助于医生指导他们的给药策略和时间安排。

该研究分为两部分。第一部分是针对三个不同阶段开发完整的希腊响应面模型:食管胃十二指肠镜检查(EGD)、结肠镜检查和检查间期(两次检查之间的时间间隔)。使用观察者警觉性评分(OAA/S)来评估患者的反应。第二部分使用这些响应面模型模拟六种具有不同特征的给药方案:仅使用咪达唑仑、咪达唑仑与阿片类药物平衡组合、高剂量阿片类药物与咪达唑仑、低剂量咪达唑仑与高剂量阿片类药物、高剂量咪达唑仑与低剂量阿片类药物,以及最后咪达唑仑与阿片类药物持续输注。为了模拟目的,选择在检查期间麻醉充分时95%概率失去反应以及在检查间期50%概率恢复意识。

患者群体的平均年龄为49.3岁。平均体重指数为21.9±2.3kg/m。约56.7%为女性,且无一例接受过腹部手术。盲肠插管率为100%。只有1例患者(3%)出现暂时性低氧血症,通过简单措施迅速得到处理。每个阶段的响应面模型显示咪达唑仑和阿芬太尼之间存在显著协同作用。咪达唑仑和阿芬太尼的平衡组合提供了充分的麻醉效果且意识恢复最快。在EGD和结肠镜检查刺激期间,最后一次推注药物后的苏醒时间为7.4分钟,在EGD模拟期间为9.1分钟。

模拟不同特征的给药方案为给药策略提供了见解。咪达唑仑 - 阿芬太尼平衡方案足以提供良好的麻醉深度和最快的意识恢复。我们相信在我们的响应面模型的帮助下,临床医生可以更灵活、精确地进行镇静。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafb/4907643/e8164ddaffa4/medi-95-e3520-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafb/4907643/df00c0c813cb/medi-95-e3520-g006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafb/4907643/20067ee8e71b/medi-95-e3520-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafb/4907643/e8164ddaffa4/medi-95-e3520-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafb/4907643/df00c0c813cb/medi-95-e3520-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafb/4907643/b253cd041107/medi-95-e3520-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafb/4907643/b5173fecb818/medi-95-e3520-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafb/4907643/20067ee8e71b/medi-95-e3520-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bafb/4907643/e8164ddaffa4/medi-95-e3520-g010.jpg

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