Optimizing Vancomycin Therapy in Critically Ill Children: A Population Pharmacokinetics Study to Inform Vancomycin Area under the Curve Estimation Using Novel Biomarkers.
Optimizing Vancomycin Therapy in Critically Ill Children: A Population Pharmacokinetics Study to Inform Vancomycin Area under the Curve Estimation Using Novel Biomarkers.
复制标题
在重症儿童中优化万古霉素治疗：一项种群药代动力学研究，可在曲线估计下使用新型生物标志物在曲线估计下为万古霉素区域提供信息。
DOI：
10.3390/pharmaceutics15051336
复制
发表时间：
2023-04-25
期刊：
影响因子：
5.4
通讯作者：
Neely MN
中科院分区：
文献类型：
--
作者：
Downes KJ;Zuppa AF;Sharova A;Neely MN
曲线下面积(AUC)指导万古霉素治疗是推荐的，但由于评估肾功能的方法不充分，危重儿童的贝叶斯AUC估计是困难的。我们前瞻性地招募了50名因疑似感染而接受万古霉素静脉注射的危重儿童，并将他们分为模型训练组(n=30)和试验组(n=20)。我们使用Pmetrics在训练组中进行非参数总体PK建模，评估新的尿液和血浆肾脏生物标志物作为万古霉素清除量的协变量。在这一组中，两室模型最好地描述了数据。在协变量测试中，基于胱抑素C的估计肾小球滤过率(EGFR)和尿中性粒细胞明胶酶相关脂蛋白(NGAL；全模型)在作为协变量纳入清除时改善了模型的可能性。然后，我们使用多模型优化来确定最佳采样时间，以估计模型试验组中每个受试者的AUC24，并比较使用非隔室分析从每个受试者的所有测量浓度计算的贝叶斯后验AUC24和AUC24。我们的完整模型提供了万古霉素AUC的准确和精确的估计(偏差2.3%，不精确度6.2%)。然而，当仅以基于cystatin C的EGFR(偏差1.8%，不精确7.0%)或基于肌酐的EGFR(偏差−2.4%，不精确6.2%)作为协变量时，AUC预测与使用简化模型时相似。所有三个模型(S)都有助于准确和精确地估计危重儿童的万古霉素AUC。
Area under the curve (AUC)-directed vancomycin therapy is recommended, but Bayesian AUC estimation in critically ill children is difficult due to inadequate methods for estimating kidney function. We prospectively enrolled 50 critically ill children receiving IV vancomycin for suspected infection and divided them into model training (n = 30) and testing (n = 20) groups. We performed nonparametric population PK modeling in the training group using Pmetrics, evaluating novel urinary and plasma kidney biomarkers as covariates on vancomycin clearance. In this group, a two-compartment model best described the data. During covariate testing, cystatin C-based estimated glomerular filtration rate (eGFR) and urinary neutrophil gelatinase-associated lipocalin (NGAL; full model) improved model likelihood when included as covariates on clearance. We then used multiple-model optimization to define the optimal sampling times to estimate AUC24 for each subject in the model testing group and compared the Bayesian posterior AUC24 to AUC24 calculated using noncompartmental analysis from all measured concentrations for each subject. Our full model provided accurate and precise estimates of vancomycin AUC (bias 2.3%, imprecision 6.2%). However, AUC prediction was similar when using reduced models with only cystatin C-based eGFR (bias 1.8%, imprecision 7.0%) or creatinine-based eGFR (bias −2.4%, imprecision 6.2%) as covariates on clearance. All three model(s) facilitated accurate and precise estimation of vancomycin AUC in critically ill children.
登录
查看更多内容
DOI：
10.1080/00365510410003723
发表时间：
2004-02-01
影响因子：
2.1
作者：
Larsson, A;Malm, J;Hansson, LO
通讯作者：
Hansson, LO
影响因子：
4.9
作者：
Pais, Gwendolyn M.;Avedissian, Sean N.;Scheetz, Marc H.
通讯作者：
Scheetz, Marc H.
影响因子：
5.4
作者：
Back, Hyun-moon;Lee, Jong Bong;Yun, Hwi-yeol
通讯作者：
Yun, Hwi-yeol
影响因子：
2.8
作者：
Kim, Hanah;Hur, Mina;Yun, Yeo-Min
通讯作者：
Yun, Yeo-Min
影响因子：
11.8
作者：
Kullar, Ravina;Davis, Susan L.;Rybak, Michael J.
通讯作者：
Rybak, Michael J.