Bastida Carla, Hernández-Tejero María, Cariqueo Marcial, Aziz Fátima, Fortuna Virginia, Sanz Miquel, Brunet Mercè, Fernández Javier, Soy Dolors
Pharmacy Department, Division of Medicines, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain.
Liver ICU, Hospital Clinic of Barcelona, University of Barcelona, IDIBAPS, CIBERehd, Barcelona, Spain.
J Antimicrob Chemother. 2022 Apr 27;77(5):1365-1371. doi: 10.1093/jac/dkac036.
Physiopathological changes in advanced cirrhosis could alter tigecycline pharmacokinetics (PK), thus affecting serum drug concentrations and compromising target attainment. We aimed to describe tigecycline PK in patients with decompensated cirrhosis and severe bacterial infections, identify the sources of PK variability and assess the performance of different dosing regimens to optimize the PK/pharmacodynamic (PD) target.
Serum concentrations and covariates were obtained from patients with severe infections under tigecycline treatment. A population PK analysis was performed using non-linear mixed-effects modelling and the final model was used to simulate tigecycline exposure to assess the PTA.
Twenty critically ill patients were enrolled in the study. Data were best described by a two-compartment linear model. Mean ± SD parameter estimates for clearance (CL), intercompartmental clearance (Q), central and peripheral volumes of distribution (V1 and V2) were 14.8 ± 11 L/h, 38.4 ± 24 L/h, 63.7 ± 14 L and 233 ± 30 L, respectively. MELD score significantly influenced tigecycline CL, and total serum proteins significantly affected V1. Monte Carlo simulations showed that tigecycline elimination is hampered as MELD score values increase, consequently requiring lower drug doses. Patients with hypoproteinaemia would have lower peak tigecycline concentrations but similar steady-state concentrations compared with patients with normoproteinaemia.
Our study confirms that tigecycline dose adjustment is needed in severe hepatic dysfunction and suggests using the MELD score for dose optimization since it is identified as a covariate that significantly influences tigecycline CL. Dosing regimens are recommended to reach several PK/PD targets considering this clinical variable and any MIC within the susceptibility range.
晚期肝硬化的生理病理变化可能改变替加环素的药代动力学(PK),从而影响血清药物浓度并影响目标达成情况。我们旨在描述失代偿性肝硬化和严重细菌感染患者的替加环素PK,确定PK变异性的来源,并评估不同给药方案的性能以优化PK/药效学(PD)目标。
从接受替加环素治疗的严重感染患者中获取血清浓度和协变量。使用非线性混合效应模型进行群体PK分析,并使用最终模型模拟替加环素暴露以评估目标达成概率(PTA)。
20名危重症患者纳入研究。数据用二室线性模型能得到最佳描述。清除率(CL)、室间清除率(Q)、中央室和外周室分布容积(V1和V2)的平均±标准差参数估计值分别为14.8±11 L/h、38.4±24 L/h、63.7±14 L和233±30 L。终末期肝病模型(MELD)评分显著影响替加环素CL,总血清蛋白显著影响V1。蒙特卡洛模拟表明,随着MELD评分值增加,替加环素消除受阻,因此需要降低药物剂量。与正常蛋白血症患者相比,低蛋白血症患者的替加环素峰值浓度较低,但稳态浓度相似。
我们的研究证实,严重肝功能不全时需要调整替加环素剂量,并建议使用MELD评分进行剂量优化,因为它被确定为显著影响替加环素CL的协变量。考虑到这一临床变量和药敏范围内的任何最低抑菌浓度(MIC),建议采用给药方案以达到多个PK/PD目标。