A previously published propofol-remifentanil response surface model does not predict patient response well in video-assisted thoracic surgery

先前发表的丙泊酚-瑞芬太尼反应面模型不能很好地预测视频辅助胸腔手术中患者的反应。

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Abstract

Modern anesthesia usually employs a hypnotic and an analgesic to produce synergistic sedation and analgesia. Two remifentanil-propofol interaction response surface models were used to predict sedation using Observer's Assessment of Alertness/Sedation (OAA/S) scores; one predicts an OAA/S <2 and the other <4. We hypothesized that both models would predict regained responsiveness (RR) after video-assisted thoracic surgery (VATS) to reduce total anesthesia time and make early extubation clinically relevant. We included 30 patients undergoing VATS received total intravenous anesthesia (TIVA) combined with thoracic epidural anesthesia (TEA). Pharmacokinetic profiles were calculated using Tivatrainer. Model predictions were compared with observations to evaluate the accuracy and precision of emergence model predictions. The mean (standard deviation) differences between when a patient responded to their name and the time when the model predicted a 50% probability of patient response were 30.80 ± 17.77 and 13.71 ± 11.35 minutes for the OAA/S <2 model and <4 model, respectively. Both models had a limited ability to predict patient response in our patients. Both models identified target concentration pairs predicting time of RR in volunteers and some elective surgeries, but another model of epidural and intravenous anesthetic combinations may be needed to predict time of RR after VATS under TIVA with TEA.

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