Chalo Daniela, Pedrosa Sara, Amorim Pedro, Silva Aura, Guedes de Pinho Paula, Correia Rui, Gouveia Sonia, Sancho Consuelo
Institute of Neurosciences of Castilla y Leon, INCyL, IBSAL, University of Salamanca, Salamanca, Spain.
Anesthesiology Department, Centro Hospitalar do Baixo Vouga, Aveiro, Portugal.
Anesth Pain Med. 2019 Sep 24;9(5):e96829. doi: 10.5812/aapm.96829. eCollection 2019 Oct.
Anesthesia induction and maintenance with propofol can be guided by target-controlled infusion (TCI) systems using pharmacokinetic (Pk) models. Physiological variables, such as changes in cardiac output (CO), can influence propofol pharmacokinetics. Knee-chest (KC) surgical positioning can result in CO changes.
This study aimed to evaluate the relationship between propofol plasma concentration prediction and CO changes after induction and KC positioning.
This two-phase prospective cohort study included 20 patients scheduled for spinal surgery. Two different TCI anesthesia protocols were administered after induction. In phase I (n = 9), the loss of consciousness (LOC) concentration was set as the propofol target concentration and CO changes following induction and KC positioning were quantified. In phase II (n = 11), based on data from phase I, two reductions in the propofol target concentration on the pump were applied after LOC and before KC positioning. Propofol plasma concentrations were measured at different moments in both phases: after induction and after KC positioning.
Schnider Pk model showed a good performance in predicting propofol concentration after induction; however, after KC positioning, when a significant drop in CO occurred, the measured propofol concentrations were markedly underestimated. Intended reductions in the propofol target concentration did not attenuate HD changes. In the KC position, there was no correlation between the propofol concentration estimated by the Pk model and the measured concentration in plasma, as the latter was much higher (P = 0.013) while CO and BIS decreased significantly (P < 0.001 and P = 0.004, respectively).
Our study showed that the measured propofol plasma concentrations during the KC position were significantly underestimated by the Schnider Pk model and were associated with significant CO decrease. When placing patients in the KC position, anesthesiologists must be aware of pharmacokinetic changes and, in addition to standard monitoring, the use of depth of anesthesia and cardiac output monitors may be considered in high-risk patients.
使用药代动力学(Pk)模型的靶控输注(TCI)系统可指导丙泊酚的麻醉诱导和维持。生理变量,如心输出量(CO)的变化,可影响丙泊酚的药代动力学。膝胸(KC)手术体位可导致CO变化。
本研究旨在评估诱导和KC体位后丙泊酚血浆浓度预测与CO变化之间的关系。
这项两阶段前瞻性队列研究纳入了20例计划行脊柱手术的患者。诱导后采用两种不同的TCI麻醉方案。在第一阶段(n = 9),将意识消失(LOC)浓度设定为丙泊酚靶浓度,并对诱导和KC体位后的CO变化进行量化。在第二阶段(n = 11),根据第一阶段的数据,在LOC后和KC体位前对泵上的丙泊酚靶浓度进行两次降低。在两个阶段的不同时刻测量丙泊酚血浆浓度:诱导后和KC体位后。
Schnider Pk模型在预测诱导后丙泊酚浓度方面表现良好;然而,在KC体位后,当CO显著下降时,测得的丙泊酚浓度被明显低估。丙泊酚靶浓度的预期降低并未减弱HD变化。在KC体位时,Pk模型估计的丙泊酚浓度与血浆中测得的浓度之间无相关性,因为后者要高得多(P = 0.013),而CO和BIS显著降低(分别为P < 0.001和P = 0.004)。
我们的研究表明,Schnider Pk模型显著低估了KC体位期间测得的丙泊酚血浆浓度,且与CO显著降低有关。当将患者置于KC体位时,麻醉医生必须意识到药代动力学变化,除了标准监测外,对于高危患者可考虑使用麻醉深度和心输出量监测仪。