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Eur J Hosp Pharm ; 2021 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-33472817


BACKGROUND: In the neonatal population, individual calculation and adjustment of vancomycin (VCM) doses has been recommended based on population pharmacokinetics (PPK) methods. OBJECTIVE: Our previous study established a Chinese neonatal VCM PPK model. The main goal of this study was to evaluate the predictive performance of this PPK model for VCM trough concentration. METHODS: The data on neonatal severe infection patients treated with VCM were retrospectively collected. The predictive performance of this PPK model was expressed using mean prediction error (MPE), mean absolute prediction error (MAPE), sensitivity and specificity. Linear regression analysis was used to compare predicted and measured VCM concentrations. We drew the receiver operating characteristic (ROC) curve to evaluate the predictive efficacy of the ratio of area under the concentration-time curve over 24 hours to minimum inhibitory concentration (AUC0-24/MIC) and trough concentration for clinical efficacy. RESULTS: A total of 40 neonates with Gram-positive bacterial sepsis were included. After VCM treatment, 32 (80%) neonates were clinically cured. Eight cases were a clinical failure: the trough concentrations and AUC0-24 were lower than that of the clinical cure patients (8.70±4.30 vs 14.30±4.50 mg/L, p=0.003; 404.30±122.80 vs 515.40±131.70, p=0.037). The measured and predicted trough concentration were 11.16 (5.96, 16.53) mg/L and 10.13 (6.61, 15.73) mg/L, respectively. The MPE and MAPE were 4.62% and 13.26% (5.30%, 25.88%), respectively. The proportion of MAPE <30% in the adjusted regimen was higher than the initial regimen (89.66% vs 65.00%, p=0.039). Predictions of sensitivity and specificity by this PPK model were 88.24% and 94.29%, respectively. The coefficients of determination of linear regression analysis were 0.9171 and 0.9009 for the initial and adjusted regimen, respectively. The AUC0-24 was correlated with the trough concentration (r=0.587, p<0.001). The ROC curve indicated that the optimal cut-off points for predicting clinical efficacy were AUC0-24/MIC >425.47 and trough concentration >9.45 mg/L. CONCLUSION: This PPK model has good predictive performance in Chinese neonatal patients. Both AUC0-24/MIC and trough concentration can predict the clinical efficacy of antibacterial treatment.

Eur J Hosp Pharm ; 2021 Jan 07.
Artigo em Inglês | MEDLINE | ID: mdl-33414258


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.