Vancomycin AUC-guided therapeutic drug monitoring to reduce nephrotoxicity: are we overlooking a simpler solution? Comment on: Oda K, Jono H, Nosaka K, Saito H. Reduced nephrotoxicity in vancomycin therapeutic drug monitoring guided by area under the concentration-time curve against trough 15-20 µg/mL concentration

In Outpatients Receiving Parenteral Vancomycin, Dosing Adjustments Produced by Area Under the Curve-Based and Trough-Based Monitoring Differ Only at the Extremes of the Therapeutic Trough Range

Area under the curve (AUC)-based vancomycin dosing reduces nephrotoxicity but is burdensome. Reviewing 115 adults receiving ≥2 weeks of outpatient vancomycin, we found AUC-based and trough-based dose adjustments discordant only for troughs <12 or >16 mg/L. Selective versus universal outpatient AUC calculation would likely offer similar benefit with reduced workload.

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Optimal exposure targets for vancomycin in the treatment of neonatal coagulase-negative Staphylococcus infection: A retrospective study based on electronic medical records

BACKGROUND

The currently advocated ratio of area under the curve (AUC) over 24 h to minimum inhibitory concentration (AUC/MIC) > 400 and AUC < 600 mg h/L as the therapeutic drug monitoring (TDM) target of vancomycin is based on data from multiple observational studies in adult patients with methicillin-resistant Staphylococcus aureus (MRSA) infection. It may not be applicable to newborns with coagulase-negative Staphylococcus (CoNS) infection. We conducted a retrospective study to identify the optimal exposure targets for vancomycin in the treatment of neonatal CoNS infection.

METHODS

Based on the inclusion and exclusion criteria, serum vancomycin concentration, demographics, clinical data, and related laboratory data of newborns who received vancomycin intravenous infusion from June 1, 2016 to February 1, 2021 were collected retrospectively. The AUC was calculated using the maximum a posteriori Bayesian (MAPB) method. The vancomycin exposure threshold of AUC/MIC for efficacy and AUC for toxicity (acute kidney injury, AKI) were determined based on receiver operating characteristic (ROC) curve analysis. The correlation between vancomycin exposure and both clinical effect and nephrotoxicity was analyzed using logistic multivariate regression.

RESULTS

In total, 153 patients and 245 vancomycin concentrations (160 trough and 85 peak concentrations) were included. The ROC curve analysis showed that the exposure thresholds of AUC/MIC for clinical efficacy and AUC for nephrotoxicity were 281 and 602 mg h/L, respectively. The multivariate regression analysis showed that AUC/MIC > 280 was a predictor of efficacy (OR: 13.960, 95% CI: 1.891-103.078, P < 0.05) and AUC > 600 mg h/L was associated with AKI (OR: 9.008, 95% CI: 2.706-29.983, P < 0.05). The vancomycin AUC/MIC threshold for treating neonatal CoNS infection with vancomycin is lower than the currently advocated AUC/MIC >400.

CONCLUSION

The optimal exposure targets for vancomycin in neonatal CoNS infection were AUC/MIC > 280 and AUC < 600 mg h/L.

A Free Open-Source Bayesian Vancomycin Dosing App for Adults: Design and Evaluation Study

Background

It has been suggested that Bayesian dosing apps can assist in the therapeutic drug monitoring of patients receiving vancomycin. Unfortunately, Bayesian dosing tools are often unaffordable to resource-limited hospitals. Our aim was to improve vancomycin dosing in adults. We created a free and open-source dose adjustment app, VancoCalc, which uses Bayesian inference to aid clinicians in dosing and monitoring of vancomycin.

Objective

The aim of this paper is to describe the design, development, usability, and evaluation of a free open-source Bayesian vancomycin dosing app, VancoCalc.

Methods

The app build and model fitting process were described. Previously published pharmacokinetic models were used as priors. The ability of the app to predict vancomycin concentrations was performed using a small data set comprising of 52 patients, aged 18 years and over, who received at least 1 dose of intravenous vancomycin and had at least 2 vancomycin concentrations drawn between July 2018 and January 2021 at Lakeridge Health Corporation Ontario, Canada. With these estimated and actual concentrations, median prediction error (bias), median absolute error (accuracy), and root mean square error (precision) were calculated to evaluate the accuracy of the Bayesian estimated pharmacokinetic parameters.

Results

A total of 52 unique patients’ initial vancomycin concentrations were used to predict subsequent concentration; 104 total vancomycin concentrations were assessed. The median prediction error was –0.600 ug/mL (IQR –3.06, 2.95), the median absolute error was 3.05 ug/mL (IQR 1.44, 4.50), and the root mean square error was 5.34.

Conclusions

We described a free, open-source Bayesian vancomycin dosing calculator based on revisions of currently available calculators. Based on this small retrospective preliminary sample of patients, the app offers reasonable accuracy and bias, which may be used in everyday practice. By offering this free, open-source app, further prospective validation could be implemented in the near future.

Antibiotic Optimization in the Intensive Care Unit

Effective antimicrobial therapy remains paramount to successful treatment of patients with critical illness, such as pneumonia and sepsis. Unfortunately, critically ill patients often exhibit altered pharmacokinetics and pharmacodynamics (PK/PD) that make this endeavor challenging. Particularly in sepsis, alterations in volume of distribution (Vd) and protein binding lead to unpredictable effects on serum levels of various antimicrobials. Additionally, metabolic pathways and excretion may be significantly impacted due to end-organ failure. These dynamic factors may increase the likelihood of deleterious effects such as treatment failure or toxicity. Meeting these challenging scenarios has led to various strategies meant to improve clinical cure without untoward consequences. Vancomycin and β-lactam antimicrobials are frequently utilized and have been the focus of dose optimization strategies including extended infusion (EI) or continuous infusion (CI). Available data suggests that administration of vancomycin by CI may reduce the risk of nephrotoxicity without increasing the risk of treatment failure, although retrospective data are largely utilized in supporting this method. Other efforts to optimize vancomycin have focused on transitioning from trough-based therapeutic drug monitoring (TDM) to area-under-the-curve: minimum inhibitory concentration (AUC:MIC) ratios. Despite the creation of more user-friendly methods of calculation and data suggesting reduced rates of nephrotoxicity, widespread implementation is limited, in part due to clinician comfort. Use of β-lactams in patients with sepsis is similarly problematic due to observational data demonstrating fluctuations in serum levels in the setting of critical illness. Implementing TDM of agents such as piperacillin-tazobactam, cefepime, and meropenem has been suggested as a method of improving time above MIC (T >MIC). This practice is limited by the lack of access to commercial assays and the failure of rigorous studies to demonstrate improved treatment success. Clinicians should be aware of these challenges and should refine their dosing strategies based on individualized patient factors to reduce treatment failure.