Han Lichy, Drover David R, Chen Marianne C, Saxena Amit R, Eagleman Sarah L, Nekhendzy Vladimir, Pritchard Angelica, Capasso Robson
Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA, United States.
Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, United States.
Front Neurosci. 2023 Jul 14;17:1144141. doi: 10.3389/fnins.2023.1144141. eCollection 2023.
Dexmedetomidine is one of the anesthetics of choice for drug induced sleep endoscopy (DISE), with advantages including limited respiratory depression, analgesia, and decreased incidence of emergence delirium. However, challenges with determining sedation levels and prolonged recovery have limited its usage. An improved understanding of the effect of dexmedetomidine on the level of sedation and the corresponding electroencephalographic (EEG) changes could help overcome these barriers.
Fifty-one patients received dexmedetomidine sedation with Richmond Agitation-Sedation Scale (RASS) score assessment and continuous EEG monitoring via SedLine for DISE. We constructed a pharmacokinetic model to determine continuous dexmedetomidine blood concentration. From the SedLine, we extracted the patient state index (PSI), and from the EEG we calculated the spectral edge frequency 95% (SEF95) and the correlation dimension (CD), a type of fractal dimension used to assess the complexity of a system. These metrics were subsequently compared against one another and with the dexmedetomidine concentration.
Our pharmacokinetic model yielded a two-compartment model with volumes of 51.8 L and 106.2 L, with clearances of 69.5 and 168.9 L/h, respectively, and a time to effect of 9 min, similar to prior studies. Based on this model, decreasing RASS score, SEF95, CD, and PSI were all significantly associated with increasing dexmedetomidine concentration ( < 0.001, = 0.006, < 0.001 respectively). The CD, SEF95, and PSI better captured the effects of increasing dexmedetomidine concentration as compared to the RASS score. Simulating dexmedetomidine concentration based on titration to target levels derived from CD and PSI confirmed commonly used dexmedetomidine infusion dosages.
Dexmedetomidine use for DISE confirmed previous pharmacokinetic models seen with dexmedetomidine. Complex EEG metrics such as PSI and CD, as compared to RASS score and SEF95, better captured changes in brain state from dexmedetomidine and have potential to improve the monitoring of dexmedetomidine sedation.
右美托咪定是药物诱导睡眠内镜检查（DISE）的首选麻醉剂之一，其优点包括呼吸抑制有限、具有镇痛作用以及谵妄发生率降低。然而，确定镇静水平和恢复时间延长方面的挑战限制了其使用。更好地了解右美托咪定对镇静水平的影响以及相应的脑电图（EEG）变化有助于克服这些障碍。
51例患者接受右美托咪定镇静，通过里士满躁动镇静量表（RASS）评分评估，并通过SedLine进行连续EEG监测以进行DISE。我们构建了一个药代动力学模型来确定右美托咪定的连续血药浓度。从SedLine中，我们提取了患者状态指数（PSI），并从EEG中计算了频谱边缘频率95%（SEF95）和关联维数（CD），CD是一种用于评估系统复杂性的分形维数。随后将这些指标相互比较，并与右美托咪定浓度进行比较。
我们的药代动力学模型产生了一个二室模型，容积分别为51.8 L和106.2 L，清除率分别为69.5和168.9 L/h，起效时间为9分钟，与先前的研究相似。基于该模型，RASS评分、SEF95、CD和PSI的降低均与右美托咪定浓度升高显著相关（分别为<0.001、=0.006、<0.001）。与RASS评分相比，CD、SEF95和PSI能更好地反映右美托咪定浓度升高的影响。根据基于CD和PSI滴定至目标水平模拟的右美托咪定浓度，证实了常用的右美托咪定输注剂量。
右美托咪定用于DISE证实了先前观察到的右美托咪定药代动力学模型。与RASS评分和SEF95相比，诸如PSI和CD等复杂的EEG指标能更好地反映右美托咪定引起的脑状态变化，并有可能改善对右美托咪定镇静的监测。
