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Predictive performance of reported vancomycin population pharmacokinetic model in patients with different renal function status, especially those with augmented renal clearance
  1. Yan-xia Yu1,
  2. Jian Lu2,
  3. Hao-di Lu3,
  4. Lan Li3,
  5. Jing-jing Li3,
  6. Lu Shi3,
  7. Lu-fen duan3,
  8. Zhi-wei Zhuang4,
  9. Su-dong Xue3,
  10. Yi Shen2,
  11. Lian Tang3
  1. 1GCP office, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
  2. 2Intensive Care Unit, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
  3. 3Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
  4. 4Emergency intensive care unit, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
  1. Correspondence to Dr Lian Tang, Pharmacy, Suzhou Municipal Hospital, Suzhou 215002, China; tanglian716{at}aliyun.com

Abstract

Background There is a significant correlation between augmented renal clearance (ARC) and lower serum trough concentrations of vancomycin (VCM) during therapy. There is a need to evaluate the predictive performance of the population pharmacokinetic (PPK) model used for individual calculation of dosage regimens in ARC patients.

Objective Our study aimed to estimate the predictive performance differences of the reported VCM PPK software JPKD-vancomycin and SmartDose in patients with varying renal function status, especially those with ARC.

Methods Patients receiving VCM treatment from May 2014 to December 2019 were enrolled, and divided into the ARC group, the normal renal function (NRF) group, and the impaired renal function (IRF) group. VCM dosage, trough concentration, area under the curve (AUC) and pharmacokinetic parameters were compared among the three groups. The predictive performance of PPK software was expressed using absolute prediction error (APE), sensitivity, specificity, and regression coefficient (r2) of linear regression analysis between the measured VCM trough concentration and the predicted trough concentration.

Results A total of 388 patients were included: 86 patients in the ARC group, 241 patients in the NRF group, and 61 patients in the IRF group. The daily dose of the adjusted regimen in the ARC group was higher than in the NRF group, but the trough concentration was significantly lower than in the NRF group (2.8±0.6 g vs 1.9±0.6 g, p<0.001; 10.5±5.1 mg/L vs 12.9±6.8 mg/L, p=0.030). The percentage of trough concentrations lower than 10 mg/L was 84.9% in the ARC group. Compared with the APE of the initial dosage regimen, the APE of the adjusted regimen calculated by JPKD was lower in the ARC group (p=0.041) and the NRF group (p<0.001). Specificity of JPKD and SmartDose in the ARC group was higher than in the NRF group (p<0.001; p<0.001). According to the linear regression analysis, the coefficients of determination (r2) were all >0.6 for the initial regimen and adjusted regimen of VCM in the ARC and NRF groups, and the r2 of the adjusted regimen of JPKD was >0.8 in the ARC and NRF groups. In the IRF group, 31.1% of patients had a change in serum creatinine (Scr) level of >50%. The r2 increased from 0.527 to 0.7347 in SmartDose and from 0.55 to 0.7802 in JPKD when using Scr at the sampling time. The ARC group showed a significant decrease in AUC (p<0.001) and an increase in clearance rate (p<0.001) when compared to the NRF group.

Conclusion ARC was significantly associated with subtherapeutic serum VCM concentration. The pharmacokinetic parameters of VCM were diverse in patients with different renal function status. The PPK model JPKD and SmartDose had a good predictive performance for predicting VCM trough concentrations of the ARC and NRF patients, especially using JPKD for prediction of the adjusted regimen. The change of Scr is a main factor affecting the accuracy of software prediction.

  • clinical medicine
  • critical care
  • drug monitoring
  • microbiology
  • pharmacy service
  • hospital
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