目的 基于群体药动学（PPK）理论建立老年感染患者替加环素PPK模型并进行评价。方法 收集2019年1月1日—2022年8月30日在南京大学医学院附属鼓楼医院住院且静脉使用替加环素的老年患者为研究对象，回顾性收集符合纳入及排除标准患者的性别、年龄、体质量、药物剂量、给药时间、治疗药物监测采样时间、血药浓度、丙氨酸氨基转移酶（ALT）、天冬氨酸氨基转移酶（AST）、碱性磷酸酶（ALP）、γ-谷氨酰转肽酶（γ-GT）、白蛋白（ALB）、直接胆红素（DBIL）、总胆红素（TBIL）、尿素氮（BUN）、肌酐（Cr）以及采用Cockcroft-Gault公式计算的肌酐清除率（CrCL）等资料。患者临床给药方案为静脉滴注替加环素50 mg或100 mg，首剂加倍，每12小时给药1次。利用非线性混合效应模型法建立PPK模型，并计算药动学参数。最终模型采用拟合优度诊断、自举法（BS）、可视化预测检验法（VPC）进行内部评价，采用拟合优度诊断、VPC和预测检验误差进行外部验证，考察最终模型的预测性能。结果 纳入108例老年患者数据，其中建模组79例患者数据，血药浓度监测点309个；外部验证组29例患者数据，血药浓度监测点87个。患者感染类型主要包括肺部感染、腹腔感染、皮肤和软组织感染。最终PPK模型为二室模型，模型参数清除率（CL）、中央室分布体积（V₁）、房室间清除率（Q）、周边室分布体积（V₂）的典型值分别为8.85 L·h^-1、50.4 L、19.1 L·h^-1、202.0 L，BUN对替加环素的CL存在显著影响，模型的内部验证和外部验证均表现良好，说明最终模型的预测性能稳定可靠。结论 建立的PPK模型为首个针对老年患者的替加环素PPK模型，可为老年患者个性化使用替加环素提供参考。

Objective Based on the population pharmacokinetic (PPK) theory, to establish a PPK model of tigecycline in elderly patients with infection and to evaluate the PPK model. Methods The elderly patients hospitalized in the Drum Tower Hospital Affiliated to Medical School of Nanjing University from January 1, 2019 to August 30, 2022 who used tigecycline intravenously were collected as research objects. The gender, age, body mass, drug dose, administration time, therapeutic drug monitoring sampling time, blood concentration, alanine aminotransferase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP) and γ-glutamyl transpeptidase (γ-GT), albumin (ALB), direct bilirubin (DBIL), total bilirubin (TBIL), blood urea nitrogen (BUN), creatinine (Cr), creatinine clearance rate (CrCL) calculated by Cockcroft Gault formula and other data. The clinical administration scheme of patients was intravenous drip of tigecycline 50 mg or 100 mg, the first dose was doubled, and the drug was administered once every 12 h. The PPK model was established by nonlinear mixed effect model, and the pharmacokinetic parameters were calculated. The final model was internally evaluated by goodness-of-fit diagnosis, bootstrap method, and visual predictive checks. The predictive performance of the final model was examined using goodness-of-fit plots, visual predictive checks, and predictive test errors for external validation. Results A total of 108 elderly patient data were included, including data from 79 patient in the modeling group with 309 blood drug concentration monitoring points, data from 29 patients in the external validation group with 87 monitoring points for blood drug concentration. The main types of infection in patients include lung infections, abdominal infections, skin and soft tissue infections. The final PPK model was a two-compartment model, and the typical estimates of clearance (CL), central ventricular volume of distribution (V₁), atrioventricular clearance (Q), and peripheral ventricular volume of distribution (V₂) were 8.85 L·h^-1, 50.4 L, 19.1 L·h^-1, and 202.0 L, respectively. BUN has a significant effect on the CL of tigecycline. Both internal and external validation of the model performed well, indicating that the predictive performance of the final model is stable and reliable. Conclusion The established PPK model is the first PPK model of tigecycline for elderly patients, which can provide a reference for the individualized use of tigecycline in elderly patients.

R969.1

国家重点研发计划资助项目（2020YFC2008303）