Background Our objectives were to: (1) determine the pharmacokinetic [PK] indices of vancomycin in pediatric patients; and (2) compare attainment of two target exposures: AUC/MIC ≥ 400 and trough concentration ≥ 15 mcg/mL. Methods The population-based PK modeling was performed using NONMEM 7.2 for children ≥ 3 months old who received vancomycin for ≥ 48 hr from 2003 to 2011. A one-compartment model with first-order kinetics was used to estimate clearance (CL), volume of distribution (Vd) and area-under-curve (AUC). Empiric Bayesian post-hoc individual parameters and Monte Carlo simulations (N=11,000) were performed. Results Analysis included 702 patients with 1660 vancomycin serum concentrations. Median age was 6.6 (interquartile range [IQR] 2.2–13.4) yr, weight 22.7 (12.6–46) kg, and baseline serum creatinine (SCr) 0.40 (0.30–0.60) mg/dL. Final model PK indices were: CL(L/h) = 0.248*Wt0.75*(0.48/SCr)0.361*(ln(age)/7.8)0.995; and Vd(L) = 0.636*Wt. Using these parameters and the observed MIC distribution, Monte Carlo simulation indicated that the initial median dose of 44 (39–52) mg/kg/day was inadequate in most subjects. Regimens of 60 mg/kg/day for subjects ≥ 12 years old and 70 mg/kg/day for those < 12 years old achieved target AUC/MIC in ~ 75% and trough concentrations ≥ 15 in ~ 45% of virtual subjects. An AUC/MIC ~ 400 corresponded to trough concentration ~ 8 to 9 mcg/mL. Conclusions Targeted exposure using vancomycin AUC/MIC, compared with trough concentrations, is a more realistic target in children. Depending on age, serum creatinine, and MIC distribution, vancomycin in a dosage of 60 to 70 mg/kg/day was necessary to achieve AUC/MIC ≥ 400 in 75% of patients.
Background. Limited studies incorporating population-based pharmacokinetic modeling have been conducted to determine pharmacodynamic indices associated with nephrotoxicity during vancomycin exposure in children. Methods. A retrospective cohort analysis was conducted from September 2003 to December 2011 at 2 hospitals. Nephrotoxicity was defined as an increase in serum creatinine concentration (SCr) by 0.5 mg/dL, or 50% increase in baseline SCr, either persisting for 2 consecutive days. A 1-compartment model with firstorder kinetics was used in NONMEM 7.2 to estimate trough concentrations (C min ) and area under the curve over 24 hours (AUC). Univariate, classification and regression tree (CART), and multivariate analyses were conducted to identify factors contributing to nephrotoxicity. [IQR,; P < .001) were significantly higher in the nephrotoxic group compared with the non-nephrotoxic group. Using CART, we discovered that subjects with doses 60 mg/kg per day and AUC >1063 mg-h/L had a significantly higher occurrence of nephrotoxicity (P = .005). Adjusting for intensive care unit stay and concomitant nephrotoxic drugs, steady-state vancomycin C min 15 mcg/mL (adjusted odds ratio [aOR], 2.5; 95% confidence interval [CI], 1.1-5.8; P = .028) and AUC 800 mg-h/L (aOR, 3.7; 95% CI, 1.2-11.0; P = .018) were associated with increased risk of nephrotoxicity. Conclusions. Our study describes the pediatric exposure-nephrotoxicity relationships for vancomycin. Vancomycin C min 15 mcg/mL and AUC 800 mg-h/L in children are independently associated with a > 2.5-fold increased risk of nephrotoxicity and may provide justification for use of alternative antibiotics in selected situations.
Purpose The study objective was to compare different body size descriptors that best estimate vancomycin Vd and clearance (CL). Methods Patients between 3 months and 21 years old who received vancomycin for ≥48 hours from 2003 to 2011 were evaluated in this matched case-control study. Cases had body mass index in the ≥85th percentile; controls were nonobese individuals who were matched by age and baseline serum creatinine (SCr). Using a 1-compartment model with first-order kinetics, Bayesian post hoc individual Vd and CL were estimated. Findings Analysis included 87 matched pairs with 389 vancomycin serum concentrations. Median ages were 10.0 (interquartile range [IQR], 4.8–15.2) years for cases (overweight and obese children) and 10.2 (IQR, 4.5–14.8) years for controls (normal-weight children). Median weights were 44.0 (IQR, 23.4–78.1) kg for cases and 31.3 (IQR, 16.8–47.1) kg for controls. Mean (SD) for the baseline SCr values were also similar between the groups: 0.51 (0.22) (IQR, 0.34–0.67) mg/dL and 0.48 (0.20) (IQR, 0.30–0.60) mg/dL for the cases and controls, respectively. Actual weight and allometric weight (ie, weight0.75) were used in the final model to estimate Vd and CL, respectively. The mean Vd and CL, based on weight, for cases were lower than controls by 0.012 L/kg and 0.014 L/kg/h, respectively. Implications In obese children, actual weight and allometric weight are reasonable, convenient estimations of body fat to use for estimating vancomycin Vd and CL, respectively. However, these pharmacokinetic differences between obese children and those with normal weights are small and may not likely to be clinically relevant in dose variation.
Background Optimal monitoring of vancomycin in children needs evaluation using the exposure target with area-under-the-curve of the serum concentrations vs. time over 24 hours (AUC). Our study objectives were to: (1) compare the accuracy and precision of vancomycin AUC estimations using two sampling strategies – one serum concentration sample (1S, near trough) versus two samples (2S, near peak and trough) against the rich sample (RS) method; and (2) determine the performance of these strategies in predicting future AUC against an internal validation sample (VS). Methods This was an retrospective cohort study using population-based pharmacokinetic modeling with Bayesian post-hoc individual estimations in NONMEM 7.2. Pediatric subjects 3 months to 21 years of age who received vancomycin ≥ 48 hours and had ≥ 3 drug samples within the first ≤ 96 hours of therapy were enrolled. Outcome measures were the accuracy, precision and internal predictive performance of AUC estimations using two monitoring strategies (i.e., 1S vs 2S) against the RS (which was derived from modeling all serum vancomycin concentrations obtained anytime during therapy), and VS (from serum concentrations obtained after 96 hours of therapy). Results Analysis included 138 subjects with 712 vancomycin serum concentrations. Median age was 6.1 (interquartile range [IQR] 2.2-12.2) yr, weight 22 (13-38) kg, and baseline serum creatinine 0.37 (0.30-0.50) mg/dL. Both accuracy and precision were improved with the 2S, compared to 1S, for AUC estimations (-2.0% vs -7.6 % and 10.3% vs 12.8%, respectively) against the RS. Improved accuracy and precision were also observed for 2S when evaluated against VS in predicting future AUC. Conclusion Compared to 1S, the 2S sampling strategy for vancomycin monitoring improved accuracy and precision in estimating and predicting future AUC. Evaluating two drug concentrations in children may be prudent to ensure adequate drug exposure.
The potency of ICS use in pediatric patients with moderate-severe asthma affects BMI trajectory; the higher the dose, the greater the projected BMI increase per year. Initiation of biologic therapy decreased BMI trajectory over time. Lastly, those with frequent ED visits had a higher BMI trend. Future prospective studies are warranted that further evaluate the potential metabolic impacts of ICS and assess the effects of biologic therapy on BMI.
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