目的:验证群体药代动力学软件JPKD-vancomycin对万古霉素稳态谷浓度的预测能力，并分析影响JPKD-vancomycin软件预测能力的因素。方法:收集2013年7月至2018年12月在南京医科大学附属苏州医院应用万古霉素抗感染治疗并同时进行血药浓度监测（TDM）的住院患者的临床资料。所有患者参考万古霉素用药指南制定经验性给药方案（初始方案），于首次给药48 h后及下一剂给药前0.5 h测定万古霉素稳态谷浓度，稳态谷浓度不达标者按谷浓度值制定个体化调整给药方案（调整方案），调整给药48 h后再次测定万古霉素稳态谷浓度；万古霉素的目标浓度为10～20 mg/L。收集患者临床信息，根据经典药代动力学软件Vancomycin Calculator测算结果，应用JPKD-vancomycin软件测算万古霉素初始方案并预测稳态谷浓度；再采用JPKD-vancomycin软件调整万古霉素给药方案并预测调整方案后的稳态谷浓度。采用万古霉素预测稳态谷浓度（Cn 预）与实测稳态谷浓度（Cn 实）的权重偏差（WRES）评估JPKD-vancomycin软件对万古霉素稳态谷浓度的预测能力。根据WRES将初始方案TDM数据分为预测准确组（WRES<30%）与预测不准确组（WRES≥30%），记录两组患者的性别、年龄、体重、身高、住院时间、合并症、应用血管活性药物、机械通气、吸烟史、是否术后、是否产科、是否创伤等指标以及实验室检查、万古霉素用药情况和TDM结果。采用单因素和多因素Logistic回归分析筛选影响JPKD-vancomycin软件预测万古霉素稳态谷浓度的因素，并绘制受试者工作特征曲线（ROC）以评价影响因素的评估价值。n 结果:共纳入310例患者，收集万古霉素TDM数据467例次，其中初始方案310例次，调整方案157例次。与初始方案相比，根据初始Cn 实调整方案后的WRES显著减小〔14.84（6.05，22.89）%比20.41（11.06，45.76）%，n P<0.01〕，WRES<30%的比例显著升高〔82.80%（130/157）比63.87%（198/310），n P<0.01〕，提示JPKD-vancomycin软件预测调整方案万古霉素稳态谷浓度的准确性优于对初始方案稳态谷浓度的预测。预测准确组198例次，预测不准确组112例次；单因素Logistic回归分析结果显示，女性〔优势比（n OR）＝0.466，95%可信区间（95%n CI）为0.290～0.746，n P＝0.002〕、体重轻（n OR＝0.974，95%n CI为0.953～0.996，n P＝0.022）、身高矮（n OR＝0.963，95%n CI为0.935～0.992，n P＝0.014）、万古霉素清除率（CLn Van）低（n OR<0.001，95%n CI为0.000～0.231，n P＝0.023）和术后患者（n OR＝1.695，95%n CI为1.063～2.702，n P＝0.027）是影响JPKD-vancomycin软件预测能力的相关因素；多因素Logistic回归分析显示，女性（n OR＝0.449，95%n CI为0.205～0.986，n P＝0.046）、CLn Van低（n OR<0.001，95%n CI为0.000～0.081，n P＝0.015）和术后患者（n OR＝2.493，95%n CI为1.455～4.272，n P＝0.001）是JPKD-vancomycin软件预测不准确的独立危险因素。ROC曲线分析显示，CLn Van评估JPKD-vancomycin软件预测万古霉素稳态谷浓度准确性的ROC曲线下面积（AUC）为0.571，当CLn Van低于0.065 L·hn -1·kgn -1时，敏感度为56.3%，特异度为57.1%，说明JPKD-vancomycin软件预测万古霉素稳态谷浓度不准确的风险增加。n 结论:JPKD-vancomycin软件对万古霉素调整给药方案后稳态谷浓度的预测能力较初始方案稳态谷浓度更高；JPKD-vancomycin软件对女性、CLn Van低和术后患者万古霉素稳态谷浓度的预测能力较差，尤其是CLn Van低于0.065 L·hn -1·kgn -1时，预测不准确的风险增加。n “,”Objective:To estimate the predictive performance of the population pharmacokinetics software JPKD-vancomycin on predicting the vancomycin steady-state trough concentration, and to analyze the related factors affecting the predictive performance.Methods:The clinical data of patients who were treated with vancomycin and received therapeutic drug monitoring (TDM) admitted to Suzhou Hospital Affiliated to Nanjing Medical University from July 2013 to December 2018 were enrolled. All patients were designed an empirical vancomycin regimen (initial regimen) according to vancomycin medication guidelines. Steady-state trough concentrations of vancomycin were determined at 48 hours after the first dose and 0.5 hour before the next dose. Dosage regimen was adjusted when steady-state trough concentration was not in 10-20 mg/L (adjustment regimen), and then the steady-state trough concentration was determined again 48 hours after adjustment. First, the JPKD-vancomycin software was used to calculate the initial regimen and predict the steady-state trough concentration according to the results calculated by classic pharmacokinetic software Vancomycin Calculator. Second, the JPKD-vancomycin software was used to adjust the vancomycin dosage regime and predict the steady-state trough concentration of adjustment regimen. The weight residual (WRES) between the predicted steady-state trough concentration (Cn pre) and the measured steady-state trough concentration (Cn real) was used to evaluate the ability of the JPKD-vancomycin software for predicting the vancomycin steady-state trough concentration. The TDM results of initial regimen were divided into accurate prediction group (WRES < 30%) and the inaccurate prediction group (WRES ≥ 30%) according to the WRES value. Patient and disease characteristics including gender, age, weight, height, the length of hospital stay, comorbidities, vasoactive agent, mechanical ventilation, smoking history, postoperative, obstetric patients, trauma, laboratory indicators, vancomycin therapy and TDM results were collected from electronic medical records. Univariate and multivariate Logistic regression analysis was used to screen the related factors that influence the predictive performance of JPKD-vancomycin software, and the receiver operating characteristic (ROC) curve was drawn to evaluate its predictive value.n Results:A total of 310 patients were enrolled, and 467 steady-state trough concentrations of vancomycin were collected, including 310 concentrations of initial regimen and 157 concentrations of adjustment regimen. Compared with the initial regimen, the WRES of adjusted regimen was significantly reduced [14.84 (6.05, 22.89)% vs. 20.41 (11.06, 45.76)%, n P < 0.01], and the proportion of WRES < 30% increased significantly [82.80% (130/157) vs. 63.87% (198/310), n P < 0.01]. These results indicated that JPKD-vancomycin software had a better accuracy prediction for steady-state trough concentration of the adjusted regimen than the initial regimen. There were 198 concentrations in the accurate prediction group and 112 in the inaccurate prediction group. Univariate Logistic regression analysis showed that women [odds ratio ( n OR) = 0.466, 95% confidence interval (95%n CI) was 0.290-0.746, n P = 0.002], low body weight (n OR = 0.974, 95%n CI was 0.953-0.996, n P = 0.022), short height (n OR = 0.963, 95%n CI was 0.935-0.992, n P = 0.014), low vancomycin clearance (CLn Van; n OR < 0.001, 95% n CI was 0.000-0.231, n P = 0.023) and postoperative patients (n OR = 1.695, 95%n CI was 1.063-2.702, n P = 0.027) were related factors affecting the predictive performance of JPKD-vancomycin software. Multivariate Logistic regression analysis indicated that women (n OR = 0.449, 95%n CI was 0.205-0.986, n P = 0.046), low CLn Van (n OR < 0.001, 95% n CI was 0.000-0.081, n P = 0.015) and postoperative patients (n OR = 2.493, 95%n CI was 1.455-4.272, n P = 0.001) were independent risk factors for inaccurate prediction of JPKD-vancomycin software. The ROC analysis indicated that the area under ROC curve (AUC) of the CLn Van for evaluating the accuracy of JPKD-vancomycin software in predicting vancomycin steady-state trough concentration was 0.571, the sensitivity was 56.3%, and the specificity was 57.1%. The predictive performance of JPKD-vancomycin software was decreased when CLn Van was lower than 0.065 L·hn -1·kgn -1.n Conclusions:JPKD-vancomycin software had a better predictive performance for the vancomycin steady-state trough concentrations of adjustment regimen than initial regimen. JPKD-vancomycin software had a poor predictive performance when the patient was female, having low CLn Van, and was postoperative. The predictive performance of JPKD-vancomycin software was decreased when CLn Van was lower than 0.065 L·hn -1·kgn -1.n