Are vancomycin trough concentrations adequate for optimal dosing?

Decreased Kidney Function Explains Higher Vancomycin Exposure in Older Adults

INTRODUCTION

Older adults face a higher risk of vancomycin-related toxicity given their (patho)-physiological changes, making early management of supratherapeutic exposure crucial. Yet, data on vancomycin exposure in older adults is scarce. This study aims to compare vancomycin concentrations between older and younger patients, emphasizing supratherapeutic concentrations and the effect of patient characteristics.

METHODS

This observational retrospective study was conducted in the University Hospital of Leuven (EC Research S65213). We analyzed early (first) vancomycin concentrations between older (≥ 75 years) and younger patients. Multivariable analyses were conducted to evaluate the association between baseline patient characteristics with supratherapeutic exposure (logistic regression), and dose-normalized concentrations (linear regression).

RESULTS

We included 449 patients aged ≥ 75 years (median 80) and 1609 aged < 75 years (median 61). In univariable analysis, the first-measured vancomycin concentrations were significantly higher in older adults (p < 0.001), who more frequently reached supratherapeutic concentrations (30.7% versus 21%; p < 0.001). In multivariable analysis, factors associated with supratherapeutic concentrations were decreased the estimated glomerular filtration rate calculated by using the Chronic Kidney Disease Epidemiology Collaboration equation (eGFRCKD-EPI) [odds ratio (OR) of 0.98, confidence interval (CI) 0.97-0.98]. Supratherapeutic concentrations had inverse association with giving lower loading dose (OR of 0.59, CI 0.39-0.90), and lower maintenance dose (OR of 0.45, CI 0.26-0.77). Factors that predicted increased dose-normalized concentrations included decreased eGFRCKD-EPI (coefficient of -0.05, CI -0.06 to -0.04), lower body weight (coefficient of -0.04, CI -0.05 to -0.03), increased blood urea nitrogen (coefficient of 0.02, CI 0.01-0.03), and delayed time to therapeutic drug monitoring (TDM) sampling (coefficient of 0.08, CI 0.06-0.09).

CONCLUSIONS

The absence of age as a significant factor in the multivariable analysis suggests that eGFRCKD-EPI mediated the relationship between age and vancomycin exposure. Older adults may benefit more from vancomycin TDM.

Determination of a vancomycin nephrotoxicity threshold and assessment of target attainment in hematology patients

An area-under-the-curve (AUC24)-based approach is recommended to guide vancomycin therapeutic drug monitoring (TDM), yet trough concentrations are still commonly used despite associated risks. A definitive toxicity target is lacking, which is important for hematology patients who have a higher risk of nephrotoxicity. The aims were to (1) assess the impact of trough-based TDM on acute kidney injury (AKI) incidence, (2) establish a vancomycin nephrotoxicity threshold, and (3) evaluate the proportion of hematology patients achieving vancomycin therapeutic targets. Retrospective data was collected from 100 adult patients with a hematological malignancy or aplastic anemia who received vancomycin between April 2020 and January 2021. AKI occurrence was determined based on serum creatinine concentrations, and individual pharmacokinetic parameters were estimated using a Bayesian approach. Receiver operating characteristic (ROC) curve analysis was performed to assess the ability of pharmacokinetic indices to predict AKI occurrence. The proportion of patients who achieved target vancomycin exposure was evaluated based on an AUC24/MIC ≥400 and the determined toxicity threshold. The incidence of AKI was 37%. ROC curve analysis indicated a maximum AUC24 of 644 mg.h/L over the treatment period was an important predictor of AKI. By Day 4 of treatment, 29% of treatment courses had supratherapeutic vancomycin exposure, with only 62% of courses achieving AUC24 targets. The identified toxicity threshold supports an AUC24 target range of 400-650 mg.h/L, assuming an MIC of 1 mg/L, to optimize vancomycin efficacy and minimize toxicity. This study highlights high rates of AKI in this population and emphasizes the importance of transitioning from trough-based TDM to an AUC-based approach to improve clinical outcomes.

Characterizing Day 1 Area Under the Curve Following Vancomycin Loading Dose Administration in Adult Hospitalized Patients Using Non-Trapezoidal Linear Pharmacokinetic Equations: A Retrospective Observational Study

INTRODUCTION

Methicillin-resistant Staphylococcus aureus (MRSA) infections are a serious threat to public health. Vancomycin (VAN) remains the primary treatment for these infections, and achieving the recommended area under the curve (AUC) target has been linked to improved clinical outcomes. The current VAN therapeutic monitoring guidelines recommend a loading dose (LD) of 20-35 mg/kg to rapidly attain targeted VAN exposures within 24 h of therapy. However, there is a paucity of data describing the impact of VAN LD on day 1 area under the curve (AUC0-24). This study aims to employ pharmacokinetic (PK) equations to calculate and describe the AUC0-24 following a VAN LD of 20 mg/kg.

METHODS

This was a retrospective study of adult patients who were loaded with VAN 20 mg/kg, received ≥ 48 h of treatment, and had two consecutive serum VAN levels collected within 24 h. Linear, non-trapezoidal PK equations and two post-infusion VAN levels were used to calculate AUC0-24. Therapeutic AUC0-24 was defined as 400-600 mg/l*h.

RESULTS

Among 123 included patients, the median age was 46 years (IQR 36, 62), 54% (67/123) of the patients had a body mass index (BMI) ≥ 30 kg/m2 and 27% (33/123) were admitted to the intensive care unit (ICU). Following a LD of 20 mg/kg, 50% (61/123) of the patients met the therapeutic AUC0-24, while 22% (27/123) of the patients were subtherapeutic, and 28% (35/123) were supratherapeutic. Compared with patients who achieved therapeutic AUC0-24, patients with subtherapeutic AUC0-24 were more likely to be younger (44 vs. 37 years old) and have a BMI ≥ 30 kg/m2 (67 vs. 52%). In contrast, patients with supratherapeutic AUC0-24 were more likely to be older (64 vs. 44 years old) and to have chronic kidney disease diagnosis (23 vs. 7%) when compared to patients who achieved a therapeutic AUC0-24. CONCLUSIONS: Only 50% of patients achieve the target AUC0-24 following a VAN 20 mg/kg LD, with younger, heavier patients underexposed and older patients with renal impairment overexposed, suggesting that different dosing strategies are needed for these populations.

Determining steady-state trough range in vancomycin drug dosing using machine learning

BACKGROUND

Vancomycin is a renally eliminated, nephrotoxic, glycopeptide antibiotic with a narrow therapeutic window, widely used in intensive care units (ICU). We aimed to predict the risk of inappropriate vancomycin trough levels and appropriate dosing for each ICU patient.

METHODS

Observed vancomycin trough levels were categorized into sub-therapeutic, therapeutic, and supra-therapeutic levels to train and compare different classification models. We included adult ICU patients (≥ 18 years) with at least one vancomycin concentration measurement during hospitalization at Mayo Clinic, Rochester, MN, from January 2007 to December 2017.

RESULT

The final cohort consisted of 5337 vancomycin courses. The XGBoost models outperformed other machine learning models with the AUC-ROC of 0.85 and 0.83, specificity of 53% and 47%, and sensitivity of 94% and 94% for sub- and supra-therapeutic categories, respectively. Kinetic estimated glomerular filtration rate and other creatinine-based measurements, vancomycin regimen (dose and interval), comorbidities, body mass index, age, sex, and blood pressure were among the most important variables in the models.

CONCLUSION

We developed models to assess the risk of sub- and supra-therapeutic vancomycin trough levels to improve the accuracy of drug dosing in critically ill patients.

Individualized, dynamic, and full-course vancomycin dosing prediction: a study on the customized dose model

Purpose

The single-point trough-based therapeutic drug monitoring (TDM) and Bayesian forecasting approaches are still limited in individualized and dynamic vancomycin delivery. Until recently, there has not yet been enough focus on the direct integration of pharmacokinetic/pharmacodynamic (PK/PD) and TDM to construct a customized dose model (CDM) for vancomycin to achieve individualized, dynamic, and full-course dose prediction from empirical to follow-up treatment. This study sought to establish CDM for vancomycin, test its performance and superiority in clinical efficacy prediction, formulate a CDM-driven full-course dosage prediction strategy to overcome the above challenge, and predict the empirical vancomycin dosages for six Staphylococci populations and four strains in patients with various creatinine clearance rates (CLcr).

Methods

The PK/PD and concentration models derived from our earlier research were used to establish CDM. The receiver operating characteristic (ROC) curve, with the area under ROC curve (AUCR) as the primary endpoint, for 21 retrospective cases was applied to test the performance and superiority of CDM in clinical efficacy prediction by comparison to the current frequently-used dose model (FDM). A model with an AUCR of at least 0.8 was considered acceptable. Based on the availability of TDM, the strategy of CDM-driven individualized, dynamic, and full-course dose prediction for vancomycin therapy was formulated. Based on the CDM, Monte Carlo simulation was used to predict the empirical vancomycin dosages for the target populations and bacteria.

Results

Four CDMs and the strategy of CDM-driven individualized, dynamic, and full-course dose prediction for vancomycin therapy from empirical to follow-up treatment were constructed. Compared with FDM, CDM showed a greater AUCR value (0.807 vs. 0.688) in clinical efficacy prediction. The empirical vancomycin dosages for six Staphylococci populations and four strains in patients with various CLcr were predicted.

Conclusion

CDM is a competitive individualized dose model. It compensates for the drawbacks of the existing TDM technology and Bayesian forecasting and offers a straightforward and useful supplemental approach for individualized and dynamic vancomycin delivery. Through mathematical modeling of the vancomycin dosage, this study achieved the goal of predicting doses individually, dynamically, and throughout, thus promoting "mathematical knowledge transfer and application" and also providing reference for quantitative and personalized research on similar drugs.

Predictive Value of Vancomycin AUC24/MIC Ratio for 30-day Mortality in Patients with Severe or Complicated Methicillin-Resistant Staphylococcus aureus Infections: A Multicenter Retrospective Study

BACKGROUND

Although vancomycin is typically employed against methicillin-resistant Staphylococcus aureus (MRSA) infections, the optimal ratio of 24-h area under the concentration-time curve to minimum inhibitory concentration (AUC24/MIC) for severe or complicated infections lacks clear guideline recommendations. This study aimed to determine the target AUC24/MIC ratio associated with treatment outcomes of infections treated with vancomycin.

METHODS

This retrospective multicenter cohort study included adult patients receiving ≥ 5 days of vancomycin for severe/complicated MRSA infections (e.g., osteoarticular, pulmonary, endocarditis, etc.) between January 2018 and December 2023. The primary outcome was 30-day mortality, with secondary outcomes including clinical success, microbiological eradication, and nephrotoxicity. Receiver operating characteristic (ROC) curve analysis was used to identify the AUC24/MIC cutoff for 30-day mortality. Multivariate regression analysis was used to determine association between AUC24/MIC and outcomes.

RESULTS

This study included 82 patients. ROC identified a target AUC24/MIC of ≥ 505 for 30-day mortality. The overall 30-day mortality rate (22.0%) was significantly higher for below average AUC24/MIC cutoff (34.1%) than for above AUC24/MIC cutoff group (9.8%). Multivariate analysis confirmed AUC24/MIC of < 505 as an independent predictor (adjusted odds ratio, 5.001; 95% confidence interval, 1.335-18.75). The clinical success rate differed significantly between below- and above-cutoff groups, whereas microbiological eradication tended to favor the above-cutoff group. The nephrotoxicity rates were comparable between groups.

CONCLUSIONS

In treating severe/complicated MRSA infections, vancomycin AUC24/MIC ratio ≥ 505 was independently associated with favorable 30-day mortality. Given the retrospective nature of this study, further prospective studies are essential to confirm the reliability of the target AUC24/MIC ratios.

Optimization of Vancomycin Initial Dosing Regimen in Neonates Using an Externally Evaluated Population Pharmacokinetic Model

BACKGROUND

Vancomycin therapeutic monitoring guidelines were revised in March 2020, and a population pharmacokinetics-guided Bayesian approach to estimate the 24-hour area under the concentration-time curve to the minimum inhibitory concentration ratio has since been recommended instead of trough concentrations. To comply with these latest guidelines, we evaluated published population pharmacokinetic models of vancomycin using an external dataset of neonatal patients and selected the most predictive model to develop a new initial dosing regimen.

METHODS

The models were identified from the literature and tested using a retrospective dataset of Canadian neonates. Their predictive performance was assessed using prediction- and simulation-based diagnostics. Monte Carlo simulations were performed to develop the initial dosing regimen with the highest probability of therapeutic target attainment.

RESULTS

A total of 144 vancomycin concentrations were derived from 63 neonates in the external population. Five of the 28 models retained for evaluation were found predictive with a bias of 15% and an imprecision of 30%. Overall, the Grimsley and Thomson model performed best, with a bias of -0.8% and an imprecision of 20.9%; therefore, it was applied in the simulations. A novel initial dosing regimen of 15 mg/kg, followed by 11 mg/kg every 8 hours should favor therapeutic target attainment.

CONCLUSIONS

A predictive population pharmacokinetic model of vancomycin was identified after an external evaluation and used to recommend a novel initial dosing regimen. The implementation of these model-based tools may guide physicians in selecting the most appropriate initial vancomycin dose, leading to improved clinical outcomes.

Evaluation of the appropriateness of vancomycin therapeutic drug monitoring in the intensive care unit with a clinical pharmacy approach, a cross-sectional study

OBJECTIVES

Vancomycin, a glycopeptide antibiotic has antibacterial activity against Gram-positive bacteria and is frequently used in the intensive care unit (ICU). Inappropriate therapeutic drug monitoring (TDM) of vancomycin is a common problem encountered in hospital daily practice. The aim of this study was to evaluate the appropriateness of vancomycin trough-guided TDM in patients treated in the ICU using a clinical pharmacy approach.

METHODS

The study was conducted retrospectively in patients over 18 years old who had at least one vancomycin trough level and who had received intravenous (IV) vancomycin for ≥3 days between 1 November 2020 and 1 April 2022. The study included 137 patients. Patient demographics and relevant vancomycin TDM data were collected from medical records. The appropriateness of TDM was evaluated according to the criteria established based on the monitoring recommendations specified in consensus guidelines for therapeutic drug monitoring of vancomycin published by the American Society of Health-System Pharmacists (ASHP) in 2009 and 2020.

RESULTS

Of a total of 238 vancomycin trough levels measured in patients, 32.4% were collected at an inappropriate time. When patients were evaluated in terms of TDM appropriateness according to vancomycin level ranges (<10 µg/mL, 10-20 µg/mL and >20 µg/mL), we found the appropriate TDM was significantly higher in the therapeutic range (10-20 µg/mL) (p <0.001). Of the total 238 vancomycin trough concentrations taken from patients, 77 (32.4%) were measured at an inappropriate time. This caused dose withholding, wrong adjustments and therapy failure. The total TDM appropriateness of vancomycin was significantly higher in the therapeutic range defined as 10-20 µg/mL when evaluated based on 'TDM appropriateness criteria' (p <0.001).

CONCLUSION

Our study shows that appropriate vancomycin TDM increases the likelihood of achieving target trough concentrations. Involvement of clinical pharmacists in TDM management may prevent the development of adverse reactions by ensuring appropriate sampling time and appropriate interpretation of vancomycin levels.

Is It Still Beneficial to Monitor the Trough Concentration of Vancomycin? A Quantitative Meta-Analysis of Nephrotoxicity and Efficacy

This study conducted a quantitative meta-analysis to investigate the association of vancomycin indicators, particularly area under the curve over 24 h (AUC24) and trough concentrations (Ctrough), and their relationship with both nephrotoxicity and efficacy. Literature research was performed in PubMed and Web of Science on vancomycin nephrotoxicity and efficacy in adult inpatients. Vancomycin Ctrough, AUC24, AUC24/minimum inhibitory concentration (MIC), nephrotoxicity evaluation and treatment outcomes were extracted. Logistic regression and Emax models were conducted, stratified by evaluation criterion for nephrotoxicity and primary outcomes for efficacy. Among 100 publications on nephrotoxicity, 29 focused on AUC24 and 97 on Ctrough, while of 74 publications on efficacy, 27 reported AUC24/MIC and 68 reported Ctrough. The logistic regression analysis indicated a significant association between nephrotoxicity and vancomycin Ctrough (odds ratio = 2.193; 95% CI 1.582-3.442, p < 0.001). The receiver operating characteristic curve had an area of 0.90, with a cut-off point of 14.55 mg/L. Additionally, 92.3% of the groups with a mean AUC24 within 400-600 mg·h/L showed a mean Ctrough of 10-20 mg/L. However, a subtle, non-statistically significant association was observed between the AUC24 and nephrotoxicity, as well as between AUC24/MIC and Ctrough concerning treatment outcomes. Our findings suggest that monitoring vancomycin Ctrough remains a beneficial and valuable approach to proactively identifying patients at risk of nephrotoxicity, particularly when Ctrough exceeds 15 mg/L. Ctrough can serve as a surrogate for AUC24 to some extent. However, no definitive cut-off values were identified for AUC24 concerning nephrotoxicity or for Ctrough and AUC24/MIC regarding efficacy.

Agreement Between Two-Concentration and One-Concentration Area Under the Curve (AUC) Estimates When Using Bayesian Modeling to Dose Vancomycin in Patients With Obesity

BACKGROUND

Vancomycin Bayesian modeling provides 24-hour area under the curve (AUC24) estimations. However, the agreement between two-concentration and one-concentration Bayesian estimates in patients with obesity is unknown.

OBJECTIVE

The purpose of this study was to determine the agreement between two-concentration and one-concentration Bayesian AUC24 estimates in patients with obesity receiving vancomycin.

METHODS

This retrospective within-subjects cohort study included patients with obesity and two vancomycin concentrations. The first concentration was hidden from dosing software to record the one-concentration AUC24. AUC24 estimates were categorized into 1 of 3 groups: <400, 400 to 600, or >600 mg*h/L. Patients were excluded for vancomycin duration less than 48 hours or renal dysfunction. The primary outcome was AUC24 agreement with two versus one concentration. Secondary outcomes included the AUC24 category, matching of AUC24 categorization, and correlation between two-concentration versus one-concentration AUC24. AUC24 estimate agreement was assessed by Bland Altman plot and bias via linear regression. Statistical analyses were performed using SPSS (version 20.0).

RESULTS

A total of 31 patients were included. The mean difference in AUC24 between two versus one concentration was 11.4 mg*h/L (95% limits of agreement = -72 to 95 mg*h/L). Linear regression indicated the presence of proportional bias at higher AUC24 values (β = 0.16; P = 0.015). Matching of AUC24 categorization with two versus one concentration was 87% (27/31 patients).

CONCLUSION AND RELEVANCE

This study demonstrated overall agreement between AUC24 estimates when using two versus one vancomycin concentration in patients with obesity, though proportional bias was detected at higher AUC24. Future studies with larger sample sizes are needed to confirm these results.

Developing an intervention package to optimise the management of vancomycin therapy using theory informed co-design

BACKGROUND

Optimising the management of vancomycin by achieving target therapeutic concentrations early during therapy has been associated with reduced mortality and morbidity. Despite the availability of guidelines and training, the management of vancomycin remains suboptimal.

OBJECTIVES

The primary outcome was the development of interventions and associated implementation strategies to optimise the management of vancomycin therapy. This paper describes how co-design process was used to build a theory informed intervention package, which was implemented across a wide range of in-patient hospital settings in Queensland, Australia.

METHODS

This multiple methods study was conducted in four phases: 1) a baseline audit to identify the nature of the problem and associated determinants informed by stakeholder interviews 2) mapping these findings to the Theoretical Domains Framework (TDF) to identify behavioural correlates and modifiers 3) prioritising the behavioural modifiers and associated implementation strategies to inform a protype of the intervention in a series of co-design sessions and 4) implementing and evaluating the intervention package. The study was conducted across the four teaching hospitals in a large Queensland Hospital and Health Service across multiple healthcare disciplines namely nurses, doctors, and pharmacists. This intervention package was subsequently implemented across Queensland Health with the support of the local champions under the guidance of the steering group.

RESULTS

Clinicians identified that a multifaceted intervention package and training which can be tailored to the health-care professional disciplines, would be best suited to shift clinician behaviour to align with guidelines. The findings from the co-design process aligned with theory-informed intervention package. Each of the intervention strategies varied in their frequency and popularity of use.

CONCLUSIONS

The use of theory-informed and participatory approach assisted with the intervention development process and aligned the intervention content with the priorities of stakeholders. The TDF provided a structured process for developing intervention content which is both acceptable and useful to stakeholders and may improve the management of vancomycin.

Out With the Old, in With the New: What Rising Pharmacists Need to Know About Vancomycin Therapeutic Drug Monitoring in Adults

The goal of this commentary is to provide recent pharmacy school graduates and student pharmacists completing APPEs the essential background for correct vancomycin therapeutic drug monitoring (TDM) in the inpatient setting.

Association between trough serum vancomycin concentration and vancomycin-associated acute kidney injury and 30-day mortality in critically ill elderly adults

BACKGROUND

Vancomycin-associated acute kidney injury (VA-AKI) is the most clinically relevant side effect of vancomycin. The objective of this study was to investigate the association between VTC and VA-AKI as well as 30-day mortality in critically ill elderly adults.

METHOD

Elderly patients with trough serum vancomycin concentration records(VTC) in the Medical Information Mart-IV (MIMIC-IV) and eICU databases were retrospectively studied.

RESULTS

A total of 3,146 critically ill elderly adults were finally enrolled. The incidence of VA-AKI in the elderly population was 76.5%. Logistic regression analysis revealed significant relationships between VA-AKI and various factors, including VTC, comorbidities, and laboratory indicators, and SOFA, and GCS score. For each mg/L increase, the OR for VA-AKI increased by 2.5%. The association between VTC and 30-day mortality was found to be statistically significant (odds ratio (OR): 1.021, 95% CI: 1.010-1.031), P < 0.001). The Restricted cubic splines (RCS) curves revealed that VTC ranged of 19.67 to 35.72 mg/l for AKI and 19.17 to 42.86 mg/l for 30-day mortality exhibit OR with 95% CI above 1, indicating statistically significant associations with an increased risk of AKI and 30-day mortality, respectively. In the subgroup analysis, VTC was identified as a risk factor for VA-AKI in specific patient groups, including white individuals, female patients, those with shock, patients with SOFA > 6, patients with baseline creatinine > 1.2 mg/dl and patients with or without exposed to other nephrotoxic medications.

CONCLUSION

This study found the significant association between VTC and the incidence of VA-AKI and 30-day mortality in critically ill elderly adults. The RCS curves indicated concentration ranges for AKI (19.67-35.72 mg/L) and 30-day mortality (19.17-42.86 mg/L), signifying increased risk.

Optimizing Antibiotic Therapy for Intravenous Drug Users: A Narrative Review Unraveling Pharmacokinetics/Pharmacodynamics Challenges

Intravenous drug users (IVDUs) face heightened susceptibility to life-threatening gram-positive bacterial infections, particularly methicillin-resistant Staphylococcus aureus (MRSA). While the standard antibiotic dosing strategies for special patients, such as obese or critically ill individuals, are known to be inadequate, raising concerns about treatment efficacy, a similar sort of understanding has not been assessed for IVDUs yet. With this in mind, this review examines the pharmacokinetic/pharmacodynamic characteristics of antibiotics commonly used against gram-positive bacteria in IVDUs. Focusing on daptomycin, vancomycin, teicoplanin, aminoglycosides, and the novel lipoglycopeptide dalbavancin, the study reveals significant pharmacokinetic variations in IVDUs, suggesting the need for personalized dosing. Concomitant opioid substitution therapy and other factors, such as malnutrition, contribute to altered pharmacokinetics/pharmacodynamics, emphasizing the importance of targeted therapeutic drug monitoring. Overall, our study calls for increased awareness among clinicians regarding the unique pharmacokinetic/pharmacodynamic challenges in IVDUs and advocates for tailored antibiotic dosing strategies to enhance treatment outcomes in this marginalized population.

Toward Model-Based Informed Precision Dosing of Vancomycin in Hematologic Cancer Patients: A First Step

BACKGROUND AND OBJECTIVE

There is no consensus on the optimal vancomycin dose to achieve pharmacokinetic/pharmacodynamic (PK/PD) target in patients with hematologic cancer or in hematopoietic stem cell transplant (HSCT) recipients. A 24-h area under the concentration-time curve (AUC) >400 mg*h/L must be achieved early for successful treatment of severe methicillin-resistant Staphylococcus aureus (MRSA) infections. Current nomograms derived from general population data are not sufficiently accurate to allow AUC-based model-informed precision dosing. The objective of this study was to characterize vancomycin PK in patients with hematologic cancer or in HSCT recipients and to develop a model-informed dosing tool based on PK/PD target requirements.

METHODS

Pooled retrospective and prospective vancomycin serum concentrations were analyzed using NONMEM® to evaluate the performance of previously published population PK (popPK) models built from hematologic cancer datasets and to develop a novel Bayesian PK model. Patients' characteristics and clinical data were tested as potential covariates. The popPK model was validated internally and externally. Predictions of vancomycin concentrations for different dosing regimens were made using Monte-Carlo simulations, and a nomogram strategy was proposed according to selected probability of target attainment (PTA).

RESULTS

The predictive performance of the published popPK models was found to be suboptimal for our population. A novel popPK model was developed using 240 vancomycin concentrations (60 patients). A two-compartment structural model with an additive error model best described the data. Ideal body weight and estimated glomerular filtration rate (eGFR) [Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)] were selected as covariates for volume of distribution (V) and clearance (CL). Bootstrapping confirmed the stability and precision of the popPK parameters. The volume of distribution was V1 = 46.8 L and V2 = 56.1 L, while CL = 5.63 L/h. External validation using 107 vancomycin concentrations (24 patients) demonstrated the predictivity of the model. A nomogram was developed to reach minimally PTA >50% for 400 < AUC < 600 mg*h/L.

CONCLUSION

To our knowledge, this study provides the first model-informed AUC-based strategy in North American hematologic cancer patients with or without HSCT. The resulting nomogram generated provides a simplified approach to improving the accuracy of initial vancomycin dosing in this population.

Model-Informed Precision Dosing Improves Outcomes in Patients Receiving Vancomycin for Gram-Positive Infections

Background

Consensus guidelines for dosing and monitoring of vancomycin recommend collection of 2 serum concentrations to estimate an area under the curve/minimum inhibitory concentration ratio (AUC/MIC). Use of Bayesian software for AUC estimation and model-informed precision dosing (MIPD) enables pre-steady state therapeutic drug monitoring using a single serum concentration; however, data supporting this approach are limited.

Methods

Adult patients with culture-proven gram-positive infections treated with vancomycin ≥72 hours receiving either trough-guided or AUC-guided therapy were included in this retrospective study. AUC-guided therapy was provided using MIPD and single-concentration monitoring. Treatment success, vancomycin-associated acute kidney injury (VA-AKI), and inpatient mortality were compared using a desirability of outcome ranking analysis. The most desirable outcome was survival with treatment success and no VA-AKI, and the least desirable outcome was death.

Results

The study population (N = 300) was comprised of an equal number of patients receiving AUC-guided or trough-guided therapy. More patients experienced the most desirable outcome in the AUC-guided group compared to the trough-guided group (58.7% vs 46.7%, P = .037). Rates of VA-AKI were lower (21.3% vs 32.0%, P = .037) and median hospital length of stay was shorter (10 days [interquartile range {IQR}, 8-20] vs 12 days [IQR, 8-25]; P = .025) among patients receiving AUC-guided therapy.

Conclusions

AUC-guided vancomycin therapy using MIPD and single-concentration monitoring improved outcomes in patients with culture-proven gram-positive infections. Safety was improved with reduced incidence of VA-AKI, and no concerns for reduced efficacy were observed. Moreover, MIPD allowed for earlier assessment of AUC target attainment and greater flexibility in the collection of serum vancomycin concentrations.

Association of vancomycin-induced acute kidney injury with trough versus AUC monitoring in patients receiving extended durations of therapy

Objective

Vancomycin therapy is associated with an increased risk of acute kidney injury (AKI). Previous studies suggest that area under the curve (AUC) monitoring reduces the risk of AKI, but literature is lacking to support this in patients receiving longer durations of vancomycin therapy.

Design

Retrospective cohort study.

Method

Patients ≥18 years old, admitted between August 2015 and July 2017 or October 2017 and September 2019, and received at least 14 days of intravenous (IV) vancomycin therapy were included in the study. Our primary outcome was the incidence of AKI between trough monitoring and AUC monitoring groups using Kidney Disease Improving Global Outcomes criteria. Secondary outcomes included inpatient mortality, median inpatient length of stay, and median intensive care unit length of stay.

Results

Overall, 582 patients were included in the study, with 318 patients included in the trough monitoring group and 264 included in the AUC monitoring group. The median duration of vancomycin therapy was 23 days (interquartile range, 16-39). Patients within the trough monitoring group had a higher incidence of AKI compared to the AUC monitoring group (45.6% vs 28.4%, p < 0.001). Furthermore, logistic regression analysis showed that AUC monitoring was associated with a 54% lower incidence of AKI (OR 0.46, 95% CI [0.31-0.69]). All-cause inpatient mortality was numerically higher in the trough monitoring group (12.9% vs 8.3%, p = 0.078).

Conclusions

In patients who received at least 14 days of IV vancomycin therapy, AUC monitoring was associated with a lower incidence of AKI.

Efficiency of dosing software using Bayesian forecasting in achieving target antibiotic exposures in critically ill patients, a prospective cohort study

INTRODUCTION

Broad-spectrum antibiotics such as beta-lactams and vancomycin are frequently used to treat critically ill patients, however, a significant number do not achieve target exposures. Therapeutic drug monitoring (TDM) combined with Bayesian forecasting dosing software may improve target attainment in these patients. This study aims to describe the efficiency of dosing software for achieving target exposures of selected beta-lactam antibiotics and vancomycin in critically ill patients.

METHODS

A prospective cohort study was undertaken in an adult intensive care unit (ICU). Patients prescribed vancomycin, piperacillin-tazobactam and meropenem were included if they exhibited a subtherapeutic or supratherapeutic exposure informed by TDM. The dosing software, ID-ODS™, was used to generate dosing recommendations which could be either accepted or rejected by the treating team. Repeat antibiotic TDM were requested to determine if target exposures were achieved.

RESULTS

Between March 2020 and December 2021, 70 were included in the analysis. Software recommendations were accepted for 56 patients (80%) with 50 having repeated antibiotic measurements. Forty-three of the 50 patients (86%) achieved target exposures after one software recommendation, with 3 of the remaining 7 patients achieving target exposures after 2. Forty-seven patients out of the 50 patients (94%) achieved the secondary outcome of clinical cure. There were no antibiotic exposure-related adverse events reported.

CONCLUSION

The use of TDM combined with Bayesian forecasting dosing software increases the efficiency for achieving target antibiotic exposures in the ICU. Clinical trials comparing this approach with other dosing strategies are required to further validate these findings.

Feasibility of individualised patient modelling for continuous vancomycin infusions in outpatient antimicrobial therapy, a retrospective study

BACKGROUND

The area under the curve (AUC) to minimum inhibitory concentration (MIC) ratio is proposed as a therapeutic drug-monitoring parameter for dosing vancomycin continuous infusion in methicillin-resistant Staphylococcus aureus (MRSA) infection. Individualised pharmacokinetic-pharmacodynamic (PK/PD) calculation of AUC24 may better represent therapeutic dosing than current Therapeutic Drug Monitoring (TDM) practices, targeting a Steady State Concentration of 15-25 mg/L.

AIM

To compare real world TDM practice to theoretical, individualised, PK/PD target parameters utilising Bayesian predictions to steady state concentrations (Css) for outpatients on continuous vancomycin infusions.

METHOD

A retrospective single centre study was conducted at a tertiary hospital on adult patients, enrolled in an outpatient parenteral antimicrobial therapy (OPAT) program, receiving vancomycin infusions for MRSA infection. Retrospective Bayesian dosing was modelled to target PK/PD parameters and compared to real world data.

RESULTS

Fifteen patients were evaluated with 53% (8/15) achieved target CSS during hospitalisation, and 83% (13/15) as outpatient. Median Bayesian AUC/MIC was 613 mg.h/L with CSS 25 mg/L. Patients suffering an Acute Kidney Injury (33%) had higher AUC0-24/MIC values. Retrospective Bayesian modelling demonstrated on median 250 mg/24 h lower doses than that administered was required (R2 = 0.81) which achieved AUC24/MIC median 444.8 (range 405-460) mg.h/L and CSS 18.8 (range 16.8-20.4) mg/L.

CONCLUSION

Bayesian modelling could assist in obtaining more timely target parameters at lower doses for patients receiving continuous vancomycin infusion as part of an OPAT program, which may beget fewer adverse effects. Utilisation of personalised predictive modelling may optimise vancomycin prescribing, achieving earlier target concentrations as compared to empiric dosing regimens.

Machine learning in medication prescription: A systematic review

BACKGROUND

Medication prescription is a complex process that could benefit from current research and development in machine learning through decision support systems. Particularly pediatricians are forced to prescribe medications "off-label" as children are still underrepresented in clinical studies, which leads to a high risk of an incorrect dose and adverse drug effects.

METHODS

PubMed, IEEE Xplore and PROSPERO were searched for relevant studies that developed and evaluated well-performing machine learning algorithms following the PRISMA statement. Quality assessment was conducted in accordance with the IJMEDI checklist. Identified studies were reviewed in detail, including the required variables for predicting the correct dose, especially of pediatric medication prescription.

RESULTS

The search identified 656 studies, of which 64 were reviewed in detail and 36 met the inclusion criteria. According to the IJMEDI checklist, five studies were considered to be of high quality. 19 of the 36 studies dealt with the active substance warfarin. Overall, machine learning algorithms based on decision trees or regression methods performed superior regarding their predictive power than algorithms based on neural networks, support vector machines or other methods. The use of ensemble methods like bagging or boosting generally enhanced the accuracy of the dose predictions. The required input and output variables of the algorithms were considerably heterogeneous and differ strongly among the respective substance.

CONCLUSIONS

By using machine learning algorithms, the prescription process could be simplified and dosing correctness could be enhanced. Despite the heterogenous results among the different substances and cases and the lack of pediatric use cases, the identified approaches and required variables can serve as an excellent starting point for further development of algorithms predicting drug doses, particularly for children. Especially the combination of physiologically-based pharmacokinetic models with machine learning algorithms represents a great opportunity to enhance the predictive power and accuracy of the developed algorithms.

Tutorial on model selection and validation of model input into precision dosing software for model-informed precision dosing

There has been rising interest in using model-informed precision dosing to provide personalized medicine to patients at the bedside. This methodology utilizes population pharmacokinetic models, measured drug concentrations from individual patients, pharmacodynamic biomarkers, and Bayesian estimation to estimate pharmacokinetic parameters and predict concentration-time profiles in individual patients. Using these individualized parameter estimates and simulated drug exposure, dosing recommendations can be generated to maximize target attainment to improve beneficial effect and minimize toxicity. However, the accuracy of the output from this evaluation is highly dependent on the population pharmacokinetic model selected. This tutorial provides a comprehensive approach to evaluating, selecting, and validating a model for input and implementation into a model-informed precision dosing program. A step-by-step outline to validate successful implementation into a precision dosing tool is described using the clinical software platforms Edsim++ and MwPharm++ as examples.

Phage Therapy, a Salvage Treatment for Multidrug-Resistant Bacteria Causing Infective Endocarditis

Infective endocarditis (IE) is defined as an infection of the endocardium, or inner surface of the heart, most frequently affecting the heart valves or implanted cardiac devices. Despite its rarity, it has a high rate of morbidity and mortality. IE generally occurs when bacteria, fungi, or other germs from another part of the body, such as the mouth, spread through the bloodstream and attach to damaged areas in the heart. The epidemiology of IE has changed as a consequence of aging and the usage of implantable cardiac devices and heart valves. The right therapeutic routes must be assessed to lower complication and fatality rates, so this requires early clinical suspicion and a fast diagnosis. It is urgently necessary to create new and efficient medicines to combat multidrug-resistant bacterial (MDR) infections because of the increasing threat of antibiotic resistance on a worldwide scale. MDR bacteria that cause IE can be treated using phages rather than antibiotics to combat MDR bacterial strains. This review will illustrate how phage therapy began and how it is considered a powerful potential candidate for the treatment of MDR bacteria that cause IE. Furthermore, it gives a brief about all reported clinical trials that demonstrated the promising effect of phage therapy in combating resistant bacterial strains that cause IE and how it will become a hope in future medicine.

Priorities and Progress in Gram-positive Bacterial Infection Research by the Antibacterial Resistance Leadership Group: A Narrative Review

The Antibacterial Resistance Leadership Group (ARLG) has prioritized infections caused by gram-positive bacteria as one of its core areas of emphasis. The ARLG Gram-positive Committee has focused on studies responding to 3 main identified research priorities: (1) investigation of strategies or therapies for infections predominantly caused by gram-positive bacteria, (2) evaluation of the efficacy of novel agents for infections caused by methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci, and (3) optimization of dosing and duration of antimicrobial agents for gram-positive infections. Herein, we summarize ARLG accomplishments in gram-positive bacterial infection research, including studies aiming to (1) inform optimal vancomycin dosing, (2) determine the role of dalbavancin in MRSA bloodstream infection, (3) characterize enterococcal bloodstream infections, (4) demonstrate the benefits of short-course therapy for pediatric community-acquired pneumonia, (5) develop quality of life measures for use in clinical trials, and (6) advance understanding of the microbiome. Future studies will incorporate innovative methodologies with a focus on interventional clinical trials that have the potential to change clinical practice for difficult-to-treat infections, such as MRSA bloodstream infections.

Population Pharmacokinetics of Vancomycin in Patients Receiving Hemodialysis in a Malian and a French Center and Simulation of the Optimal Loading Dose

PURPOSE

Vancomycin dosing remains challenging in patients receiving intermittent hemodialysis, especially in developing countries, where access to therapeutic drug monitoring and model-based dose adjustment services is limited. The objectives of this study were to describe vancomycin population PK in patients receiving hemodialysis in a Malian and French center and examine the optimal loading dose of vancomycin in this setting.

METHODS

Population pharmacokinetic analysis was conducted using Pmetrics in 31 Malian and 27 French hemodialysis patients, having a total of 309 vancomycin plasma concentrations. Structural and covariate analyses were based on goodness-of-fit criteria. The final model was used to perform simulations of the vancomycin loading dose, targeting a daily area under the concentration-time curve (AUC) of 400-600 mg.h/L or trough concentration of 15-20 mg/L at 48 hours.

RESULTS

After 48 hours of therapy, 68% of Malian and 63% of French patients exhibited a daily AUC of <400. The final model was a 2-compartment model, with hemodialysis influencing vancomycin elimination and age influencing the vancomycin volume distribution. Younger Malian patients exhibited a lower distribution volume than French patients. Dosing simulation suggested that loading doses of 1500, 2000, and 2500 mg would be required to minimize underexposure in patients aged 30, 50, and 70 years, respectively.

CONCLUSIONS

In this study, a low AUC was frequently observed in hemodialysis patients in Mali and France after a standard vancomycin loading dose. A larger dose is necessary to achieve the currently recommended AUC target. However, the proposed dosing algorithm requires further clinical evaluation.

Vancomycin dosing in high-intensity continuous renal replacement therapy: A retrospective cohort study

INTRODUCTION

An inverse relationship exists between vancomycin serum concentrations and the intensity of continuous renal replacement therapy (CRRT), reflected through the dialysate flow rate (DFR). There remains a lack of evidence to guide initial vancomycin dosing in the setting of high-intensity CRRT (i.e., DFR >30 mL/kg/h). Additionally, recommendations for pharmacokinetic monitoring of vancomycin have transitioned from a trough-based to area under the curve (AUC)-based dosing strategy to optimize efficacy and safety. Therefore, an improved understanding of the impact of CRRT intensity on AUC/MIC (minimum inhibitory concentration) has the potential to enhance vancomycin dosing in this patient population.

OBJECTIVES

The goal of this study is to evaluate current vancomycin dosing strategies and achievement of pharmacokinetic targets in patients on high-intensity CRRT.

METHODS

This was a single-center, retrospective cohort study of adult critically ill patients admitted to Houston Methodist Hospital between May 2019 and October 2021 and received vancomycin therapy while on high-intensity CRRT. High-intensity CRRT was defined by a DFR that was both ≥3 L/h and >30 mL/kg/h. Depending on the initial vancomycin dosing strategy, patients were stratified into either the traditional (15 mg/kg/day) or enhanced (≥15 mg/kg/day) dosing group. The primary outcome was the percent of patients who attained steady-state AUC24 /MIC ≥400 mg*h/L at the first obtained vancomycin level in the enhanced group compared with the traditional group.

RESULTS

A total of 125 patients were included in the final analysis, 56 in the traditional and 69 in the enhanced dosing group. The primary end point occurred in 74% and 54% of patients in the enhanced and traditional dosing groups, respectively (p = 0.029). Therapeutic vancomycin trough levels (10-20 μg/mL) were more commonly achieved in the enhanced dosing group compared with the traditional dosing group (66.7% vs. 45%, p = 0.013). As DFR rose, increasingly higher doses of vancomycin, up to 27 mg/kg/day, were required to achieve the therapeutic targets.

CONCLUSION

This is the first study to evaluate the influence of variable CRRT intensities on vancomycin AUC/MIC. Our findings suggest that vancomycin doses of ≥15 mg/kg/day are needed to achieve early therapeutic targets in patients on high-intensity CRRT.

Contemporary pharmacologic treatments of MRSA for hospitalized adults: rationale for vancomycin versus non-vancomycin therapies as first line agents

INTRODUCTION

Methicillin-resistant Staphylococcus aureus (MRSA) remains an important pathogen in the hospital setting and causes significant morbidity and mortality each year. Since the initial discovery over 60 years ago, vancomycin has remained a first-line treatment for many different types of MRSA infections. However, significant concerns related to target attainment and nephrotoxicity have spurred efforts to develop more effective agents in the last two decades.

AREAS COVERED

Newer anti-MRSA antibiotics that have been approved since 2000 include linezolid, daptomycin, and ceftaroline. As clinical evidence has accumulated, these newer agents have become more frequently used, and some are now recommended as co-first-line options (along with vancomycin) in clinical practice guidelines. For this review, a scoping review of the literature was conducted to support our findings and recommendations.

EXPERT OPINION

Vancomycin remains an important standard of care for MRSA infections but is limited with respect to nephrotoxicity and rapid target attainment. Newer agents such as linezolid, daptomycin, and ceftaroline have specific indications for treating different types of MRSA infections; however, newer agents also have unique attributes which require consideration during therapy.

Simulation of Vancomycin Exposure Using Trough and Peak Levels Achieves the Target Area under the Steady-State Concentration-Time Curve in ICU Patients

The therapeutic drug monitoring (TDM) of vancomycin (VCM) in critically ill patients often results in the estimated area being under the concentration-time curve (AUC) values that deviate from individual observations. In this study, we investigated the factors influencing the achievement of the target AUC of VCM at steady-state in critically ill patients. We retrospectively collected data from patients treated with VCM in an intensive care unit (ICU). Multivariate analysis was used to adjust for significant factors with p < 0.05 and identify new factors affecting the achievement of the target AUC at steady-state for VCM. Among the 113 patients included in this study, 72 (64%) were in the 1-point group (trough only), whereas 41 (36%) were in the 2-point group (trough/peak). The percentage of patients achieving the target AUC at the follow-up TDM evaluation was significantly higher in the two-point group. Multivariate analysis showed that being in the 2-point group and those with a 20% or more increase (or decrease) in creatinine clearance (CCr) were both significantly associated with the success rate of achieving the target AUC at the follow-up TDM. Novel findings revealed that in patients admitted to the ICU, changes in renal function were a predictor of AUC deviation, with a 20% or more increase (or decrease) in CCr being an indicator. We believe the indicators obtained in this study are simple and can be applied clinically in many facilities. If changes in renal function are anticipated, we recommend an AUC evaluation of VCM with a two-point blood collection, close monitoring of renal function, and dose adjustment based on reanalyzing the serum concentrations of VCM.

Performance of Bayesian Area Under the Concentration-Time Curve-Based Pharmacokinetic Dosing Based on a One-Compartment Model and Trough-Only Monitoring for Vancomycin

A novel Bayesian method was developed to interpret serum vancomycin concentrations (SVCs) following the administration of one or more vancomycin doses with potential varying doses and intervals based on superposition principles. The method was evaluated using retrospective data from 442 subjects from three hospitals. The patients were required to receive vancomycin for more than 3 days, have stable renal function (fluctuation in serum creatinine of ≤0.3 mg/dL), and have at least 2 trough concentrations reported. Pharmacokinetic parameters were predicted using the first SVC, and the fitted parameters were then used to predict subsequent SVCs. Using only covariate-adjusted population prior estimates, the first two SVC prediction errors were 47.3 to 54.7% for the scaled mean absolute error (sMAE) and 62.1 to 67.8% for the scaled root mean squared error (sRMSE). "Scaled" refers to the division of the MAE or RMSE by the mean value. The Bayesian method had minimal errors for the first SVC (by design), and for the second SVC, the sMAE was 8.95%, and the sRMSE was 36.5%. The predictive performance of the Bayesian method did degrade with subsequent SVCs, which we attributed to time-dependent pharmacokinetics. The 24-h area under the concentration-time curve (AUC) was determined from simulated concentrations before and after the first SVC was reported. Prior to the first SVC, 170 (38.4%) patients had a 24-h AUC of <400 mg · h/L, 186 (42.1%) had a 24-h AUC within the target range, and 86 (19.5%) had a 24-h AUC of >600 mg · h/L. After the first SVC was reported, 322 (72.9%) had a 24-h AUC within the target range, 68 (15.4%) had low values, and 52 (11.8%) had high values based on the model simulation. Target attainments were 38% before the first SVC and 73% after the first SVC. The hospitals had no policies or procedures in place for targeting 24-h AUCs, although the trough target was typically 13 to 17 mg/L. Our data provide evidence of time-dependent pharmacokinetics, which will require regular therapeutic drug monitoring regardless of the method used to interpret SVCs.

Vancomycin-loaded silk fibroin microspheres in an injectable hydrogel for chronic osteomyelitis therapy

Introduction: Chronic osteomyelitis remains a clinical challenge in orthopedics. Methods: In this study, silk fibroin microspheres (SFMPs) loaded with vancomycin are entrapped in an injectable silk hydrogel to form a vancomycin delivery system for treatment of chronic osteomyelitis. Results and Discussion: Vancomycin showed continuous release from the hydrogel for up to 25 days. The hydrogel shows strong antibacterial activity against both Escherichia coli and Staphylococcus aureus and a long antibacterial duration of 10 days without a decrease in the antibacterial effect. The injection of vancomycin-loaded silk fibroin microspheres entrapped in the hydrogel into the infected site of rat tibia reduced bone infection and improved bone regeneration compared with other treatment groups. Conclusion: Thus, the composite SF hydrogel features a sustained-release profile and good biocompatibility, making it promising for application in osteomyelitis treatment.

Association Between Vancomycin AUC and Clinical Failure in Patients with Streptococcal Bacteremia

Background: Monitoring of vancomycin using the area under the curve (AUC) to minimum inhibitory concentration (MIC) ratio is now preferred for serious methicillin-resistant Staphylococcus aureus infections. Vancomycin AUC/MIC monitoring is being investigated but is not yet well elucidated with other bacterial pathogens. Methods: A retrospective cross-sectional study was conducted assessing patients with streptococcal bacteremia treated with vancomycin definitive therapy. AUC was calculated using a Bayesian approach, and classification and regression tree analysis was used to identify a vancomycin AUC threshold predictive of clinical failure. Results: Eleven patients had a vancomycin AUC < 329 of which 8 (73%) experienced clinical failure, while 35 patients had a vancomycin AUC ≥ 329 of which 12 (34%) experienced clinical failure (P = .04). Hospital length of stay was longer in the AUC ≥ 329 group (15 vs 8 days, P = .05), whereas time to bacteremia clearance (29 [22-45] vs 25 [20-29] hours, P = .15) and toxicity incidence (13% vs 4%, P = 1) were similar between groups. Conclusions: This study identified a VAN AUC threshold of <329 to be predictive of clinical failure in patients with streptococcal bacteremia which should be interpreted as hypothesis-generating. Studies evaluating VAN AUC-based monitoring for streptococcal bloodstream infections along with other infection types are needed before implementation into clinical practice can be recommended.

Altered Pharmacokinetics Parameters of Vancomycin in Patients with Hematological Malignancy with Febrile Neutropenia, a Bayesian Software Estimation

The pharmacokinetics of vancomycin vary significantly between specific groups of patients, such as critically ill patients and patients with hematological malignancy (HM) with febrile neutropenia (FN). Recent evidence suggests that the use of the usual standard dose of antibiotics in patients with FN may not offer adequate exposure due to pharmacokinetic variability (PK). Therefore, the purpose of this study is to assess the effect of FN on AUC_0-24 as a key parameter for vancomycin monitoring, as well as to determine which vancomycin PK parameters are affected by the presence of FN using Bayesian software PrecisePK in HM with FN. This study was carried out in King Abdulaziz Medical City. All adult patients who were admitted to the Princess Norah Oncology Center PNOC between 1 January and 2017 and 31 December 2020, hospitalized and received vancomycin with a steady-state trough concentration measured before the fourth dose, were included. During the trial period, 297 patients received vancomycin during their stay at the oncology center, 217 of them meeting the inclusion criteria. Pharmacokinetic parameters were estimated for the neutropenic and non-FN patients using the precise PK Bayesian platform. The result showed that there was a significant difference (p < 0.05) in vancomycin clearance Cl_van, the volume of distribution at a steady-state V_dss, the volume of distribution for peripheral compartment V_dp, half-life for the elimination phase t½_β, and the first-order rate constant for the elimination process β in FN compared to non-FN patients. Furthermore, AUC_0-24 was lower for FN patients compared to non-FN patients, p < 0.05. FN has a significant effect on the PK parameters of vancomycin and AUC_0-24, which may require specific consideration during the treatment initiation.

Bayesian prediction-based individualized dosing of anti-methicillin-resistant Staphylococcus aureus treatment: Recent advancements and prospects in therapeutic drug monitoring

As one of the efficient techniques for TDM, the population pharmacokinetic (popPK) model approach for dose individualization has been developed due to the rapidly growing innovative progress in computer technology and has recently been considered as a part of model-informed precision dosing (MIPD). Initial dose individualization and measurement followed by maximum a posteriori (MAP)-Bayesian prediction using a popPK model are the most classical and widely used approach among a class of MIPD strategies. MAP-Bayesian prediction offers the possibility of dose optimization based on measurement even before reaching a pharmacokinetically steady state, such as in an emergency, especially for infectious diseases requiring urgent antimicrobial treatment. As the pharmacokinetic processes in critically ill patients are affected and highly variable due to pathophysiological disturbances, the advantages offered by the popPK model approach make it highly recommended and required for effective and appropriate antimicrobial treatment. In this review, we focus on novel insights and beneficial aspects of the popPK model approach, especially in the treatment of infectious diseases with anti-methicillin-resistant Staphylococcus aureus agents represented by vancomycin, and discuss the recent advancements and prospects in TDM practice.

Evaluation of Vancomycin TDM Strategies: Prediction and Prevention of Kidney Injuries Based on Vancomycin TDM Results

The current guidelines for therapeutic drug monitoring (TDM) of vancomycin suggest a target 24-hour area under the curve (AUC_0-24) of 400 to 600 mg*h/L for serious methicillin-resistant Staphylococcus aureus infections. In this study, the predictabilities of acute kidney injury (AKI) of various TDM target parameters, target levels, and sampling methods were evaluated in patients who underwent TDM from January 2020 to December 2020. The AUC_0-24 and trough values were calculated by both one- and two-point sampling methods, and were evaluated for the predictability of AKI. Among the AUC_0-24 cutoff comparisons, the threshold value of 500 mg*h/L in the two sampling methods was statistically significant (P = 0.042) when evaluated for the predictability of AKI. Analysis by an receiver operating characteristic curve estimated an AUC_0-24 cutoff value of 563.45 mg*h/L as a predictor of AKI, and was proposed as the upper limit of TDM target.

Development and Evaluation of a Novel Software Program, SAKURA-TDM, for Area Under the Concentration-Time Curve-Guided Vancomycin Dosing: A Short Communication

BACKGROUND

The area under the concentration-time curve (AUC)-guided dosing of vancomycin has been introduced in Japan; however, the optimal dosing method remains controversial. Here, a novel software program was developed for AUC-guided vancomycin dosing and to estimate the theoretical threshold of the steady-state AUC 24 that could reduce the risk of renal injury.

METHODS

A single-center, retrospective, observational study was conducted to develop a novel software program (SAKURA-TDM ver.1.0) for AUC-guided dosing. The estimation accuracy of pharmacokinetic parameters determined using SAKURA-TDM was compared with that of clinically available software programs and assessed with Bland-Altman analysis. In addition, theoretical cutoff points of the steady-state AUC 24 and the predicted trough values were estimated using Youden J statistic approach.

RESULTS

The estimation accuracy of pharmacokinetic parameters and AUC determined using SAKURA-TDM was comparable to that of other TDM software programs. Of note, despite a good relationship between the predicted AUC 24 and trough values, the correlation between the predicted AUC 24 and measured trough values was not strong. The cutoff values of the steady-state AUC 24 and the predicted trough value for reducing the probability of a measured trough value of >20 mcg/mL were 513.1 mg·h/L and 15.6 mcg/mL, respectively.

CONCLUSIONS

We demonstrated the equivalence of the estimated PK parameters between SAKURA-TDM and other TDM software programs available in Japan. Considering the threshold of both trough values and the steady-state AUC and monitoring of the AUC in a non-steady state, it would be possible to reduce the risk of vancomycin-associated renal injury.

Vancomycin use for haemodialysis patients-Development of a new dosing protocol

AIM

To develop a dosing and monitoring protocol to achieve therapeutic vancomycin levels on intermittent haemodialysis.

METHODS

We identified 15 vancomycin treatment courses received by patients on intermittent haemodialysis at a district health board in Auckland, New Zealand. Demographic, biochemical and clinical parameters were gathered from their health records. We subsequently devised and implemented a new vancomycin protocol consisting of weight-based loading dose, and subsequent dose titration according to same-day measured pre-dialysis levels. We then re-audited 16 vancomycin treatment courses to assess the performance of the protocol.

RESULTS

A significantly higher proportion of vancomycin levels were within the target range (15-20 mg/L) following the implementation of protocol, from 23% to 46% (p < .005). Additionally, a greater proportion of treatment courses had >50% of pre-dialysis levels within the target range, rising from 13% to 56% (p < .01). In the pre-protocol group, 19 out of 117 doses of vancomycin were withheld during treatment, compared to 1 out of 118 doses in the post-protocol group. A total of 62% of total maintenance doses were administered in adherence to protocol. Length of hospital stay and number of positive blood cultures while on treatment were reduced.

CONCLUSIONS

Our initial audit revealed deficiencies in our clinical practice in the absence of a local vancomycin protocol for patients receiving intermittent haemodialysis. Following the implementation of our novel protocol, there was an improvement in therapeutic levels and fewer doses were withheld. Our sample size was too small to allow for interpretation of clinical outcome data.

Safety and Feasibility Assessment of a Pharmacy-Driven AUC/MIC Vancomycin Dosing Protocol in a Multicenter Hospital System

Vancomycin is used for Gram-positive infections, including methicillin-resistant Staphylococcus aureus. The 2020 vancomycin guidelines described by M. J. Rybak, J. Le, T. P. Lodise, D. P. Levine, et al. (Am J Health Syst Pharm 77:835-864, 2020, https://doi.org/10.1093/ajhp/zxaa036) provided an update on vancomycin dosing, which recommended an optimal area under the concentration-time curve over 24 h to MIC (AUC/MIC) target of 400 to 600. In 2021, a pharmacy-driven AUC/MIC vancomycin dosing protocol was implemented across 12 Sentara Health System hospitals. The primary objective of this study was to assess if the pharmacy-driven AUC/MIC vancomycin dosing protocol led to fewer acute kidney injury (AKI) events than trough-based dosing. Secondary objectives included vancomycin duration, hospital length of stay, administered vancomycin dose during admission, vancomycin labs drawn during standard lab times, and cost. AKI was assessed in two separate ways: (i) modified AKIN (Acute Kidney Injury Network) criteria and (ii) a modified version from the vancomycin guidelines. Inferential statistics were used to analyze the results of this retrospective study. Per the AKIN definition, the rates of AKI were 13.9% (349/2,507) in the trough-based group and 14.9% (369/2,471) in the AUC/MIC-based group (P = 0.309). Per the definition of the vancomycin guidelines, the rates of AKI were 6.7% (169/2,507) in the trough-based group and 7.6% (187/2,471) in the AUC/MIC-based group (P = 0.258). A total of 52% (2,679/5,151) of vancomycin labs were obtained during standard lab times in the AUC group and 24% (1,144/4,766) in the trough group (P < 0.05). There was no difference in AKI events between AUC and trough dosing. Use of contrast dye may confound these results. AUC/MIC dosing was associated with more lab draws during standard times, a larger number of labs drawn per person, and less total use of vancomycin. IMPORTANCE In this article, we report that there were no differences in rates of acute kidney injury between trough-based vancomycin dosing and AUC/MIC-based vancomycin dosing across 12 hospitals. AUC/MIC dosing resulted in more vancomycin lab draws during standard lab draw times compared to trough dosing, thus making it more convenient for health care personnel. This study includes all uses for vancomycin, including empirical use, and all patient severity levels. Therefore, this research reflects real-world use of vancomycin in hospitals. AUC/MIC dosing is supported by various infectious disease societies. However, the feasibility of incorporating AUC/MIC dosing in hospitals is undetermined. This study is unique in that it includes hospitals of various sizes (small community hospitals and an academic teaching hospital), and it includes a feasibility component. Therefore, this study has broad applicability to other hospitals across the United States. This original research includes the clinical application of vancomycin in a multicenter health system.

Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients

In individualized therapy, the Bayesian approach integrated with population pharmacokinetic models (PopPK) for predictions together with therapeutic drug monitoring (TDM) to maintain adequate objectives is useful to maximize the efficacy and minimize the probability of toxicity of vancomycin in critically ill patients. Although there are limitations to implementation, model-informed precision dosing (MIPD) is an approach to integrate these elements, which has the potential to optimize the TDM process and maximize the success of antibacterial therapy. The objective of this work was to present an app for individualized therapy and perform a validation of the implemented vancomycin PopPK models. A pragmatic approach was used for selecting the models of Llopis, Goti and Revilla for developing a Shiny app with R. Through ordinary differential equation (ODE)-based mixed effects models from the mlxR package, the app simulates the concentrations' behavior, estimates whether the model was simulated without variability and predicts whether the model was simulated with variability. Moreover, we evaluated the predictive performance with retrospective trough concentration data from patients admitted to the adult critical care unit. Although there were no significant differences in the performance of the estimates, the Llopis model showed better accuracy (mean 80.88%; SD 46.5%); however, it had greater bias (mean -34.47%, SD 63.38%) compared to the Revilla et al. (mean 10.61%, SD 66.37%) and Goti et al. (mean of 13.54%, SD 64.93%) models. With respect to the RMSE (root mean square error), the Llopis (mean of 10.69 mg/L, SD 12.23 mg/L) and Revilla models (mean of 10.65 mg/L, SD 12.81 mg/L) were comparable, and the lowest RMSE was found in the Goti model (mean 9.06 mg/L, SD 9 mg/L). Regarding the predictions, this behavior did not change, and the results varied relatively little. Although our results are satisfactory, the predictive performance in recent studies with vancomycin is heterogeneous, and although these three models have proven to be useful for clinical application, further research and adaptation of PopPK models is required, as well as implementation in the clinical practice of MIPD and TDM in real time.

Doing More With Less: Pragmatic Implementation of Vancomycin Area-Under-the-Curve (AUC) Monitoring

Universal area-under-the-curve (AUC) guided vancomycin therapeutic drug monitoring (TDM) is resource-intensive, cost-prohibitive, and presents a paradigm shift that leaves institutions with the quandary of defining the preferred and most practical method for TDM. We report a step-by-step quality improvement process using 4 plan-do-study-act (PDSA) cycles to provide a framework for development of a hybrid model of trough and AUC-based vancomycin monitoring. We found trough-based monitoring a pragmatic strategy as a first-tier approach when anticipated use is short-term. AUC-guided monitoring was most impactful and cost-effective when reserved for patients with high-risk for nephrotoxicity. We encourage others to consider quality improvement tools to locally adopt AUC-based monitoring.

The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA

The AUC_0-24 is the most accurate way to track the vancomycin level while the C_min is not an accurate surrogate. Most hospitals in Saudi Arabia are under-practicing the AUC-guided vancomycin dosing and monitoring. No previous work has been conducted to evaluate such practice in the whole kingdom. The current study objective is to calculate the AUC_0-24 using the Bayesian dosing software (PrecisePK), identify the probability of patients who receive the optimum dose of vancomycin, and evaluate the accuracy and precision of the Bayesian platform. This retrospective study was conducted at King Abdulaziz medical city, Jeddah. All adult patients treated with vancomycin were included. Pediatric patients, critically ill patients requiring ICU admission, patients with acute renal failure or undergoing dialysis, and febrile neutropenic patients were excluded. The AUC_0-24 was predicted using the PrecisePK platform based on the Bayesian principle. The two-compartmental model by Rodvold et al. in this platform and patients' dose data were utilized to calculate the AUC_0-24 and trough level. Among 342 patients included in the present study, the mean of the estimated vancomycin AUC_0-24 by the posterior model of PrecisePK was 573 ± 199.6 mg, and the model had a bias of 16.8%, whereas the precision was 2.85 mg/L. The target AUC_0-24 (400 to 600 mg·h/L) and measured trough (10 to 20 mg/L) were documented in 127 (37.1%) and 185 (54%), respectively. Furthermore, the result demonstrated an increase in odds of AUC_0-24 > 600 mg·h/L among trough level 15-20 mg/L group (OR = 13.2, p < 0.05) as compared with trough level 10-14.9 mg/L group. In conclusion, the discordance in the AUC_0-24 ratio and measured trough concentration may jeopardize patient safety, and implantation of the Bayesian approach as a workable alternative to the traditional trough method should be considered.

Area-Under-Curve-Guided Versus Trough-Guided Monitoring of Vancomycin and Its Impact on Nephrotoxicity: A Systematic Review and Meta-Analysis

BACKGROUND

Conventionally, vancomycin trough levels have been used for therapeutic drug monitoring (TDM). Owing to the increasing evidence of trough levels being poor surrogates of area under the curve (AUC) and the advent of advanced pharmacokinetics software, a paradigm shift has been made toward AUC-guided dosing. This study aims to evaluate the impact of AUC-guided versus trough-guided TDM on vancomycin-associated nephrotoxicity.

METHODS

A systematic review was conducted using PubMed, Embase, Web of Science, Cumulative Index to Nursing and Allied Health Literature, Google scholar, and Cochrane library databases; articles published from January 01, 2009, to January 01, 2021, were retrieved and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Studies that evaluated trough-guided or AUC-guided vancomycin TDM and vancomycin-associated nephrotoxicity were included. Random-effects models were used to compare the differences in nephrotoxicity.

RESULTS

Of the 1191 retrieved studies, 57 were included. Most studies included adults and older adults (n = 47, 82.45%). The pooled prevalence of nephrotoxicity was lower in AUC-guided TDM [6.2%; 95% confidence interval (CI): 2.9%-9.5%] than in trough-guided TDM (17.0%; 95% CI: 14.7%-19.2%). Compared with the trough-guided approach, the AUC-guided approach had a lower risk of nephrotoxicity (odds ratio: 0.53; 95% CI: 0.32-0.89). The risk of nephrotoxicity was unaffected by the AUC derivation method. AUC thresholds correlated with nephrotoxicity only within the first 96 hours of therapy.

CONCLUSIONS

The AUC-guided approach had a lower risk of nephrotoxicity, supporting the updated American Society of Health-System Pharmacists guidelines. Further studies are needed to evaluate the optimal AUC-derivation methods and clinical utility of repeated measurements of the AUC and trough levels of vancomycin.

Evaluation of Limited Sampling Strategies for Bayesian Estimation of Daptomycin Area Under the Concentration-Time Curve: A Short Communication

PURPOSE

Increasing evidence supports daptomycin therapeutic drug monitoring. The author's reference center used to perform therapeutic drug monitoring in patients who receive high-dose daptomycin for bone and joint infections, with a three-sample strategy to estimate the daptomycin daily area under the concentration-time curve (AUC). The objective of this study was to evaluate simpler strategies based on only 2 or 1 sample(s).

METHODS

The authors used the BestDose software to estimate the daptomycin AUC after Bayesian posterior estimation of individual pharmacokinetic (PK) parameters at steady state. The reference AUC (AUCfull) was based on 3 samples obtained predose (T0) and approximately 1 hour (T1) and 6 hours (T6) after the start of a 30-minute infusion of IV daptomycin. It was compared with the AUC based on all possible 2-sample and 1-sample strategies. Bias, imprecision, regression, and Bland-Altman plots were used to assess the performance of the alternative strategies.

RESULTS

Data from 77 patients were analyzed. The mean AUCfull value was 936 ± 373 mg·h/L. The best 2-sample strategy was T0 + T6, with a mean prediction bias of 0.13 mg·h/L and absolute imprecision of 3%. The T0 + T1 strategy also performed well with a mean bias of -10 mg·h/L and imprecision of 3%. The best 1-sample strategy was the T6 sample only with a bias of 2.19 mg·h/L and imprecision of 6%.

CONCLUSIONS

Bayesian estimation of daptomycin AUC based on a two-sample strategy was associated with negligible bias and imprecision compared with the author's usual three-sample strategy. The trough and peak strategy may shorten and simplify patient visits and reduce assay labor and costs.

A Brief Review of Pharmacokinetic Assessments of Vancomycin in Special Groups of Patients with Altered Pharmacokinetic Parameters

Vancomycin is considered the drug of choice against many Gram-positive bacterial infections. Therapeutic drug monitoring (TDM) is essential to achieve an optimum clinical response and avoid vancomycin-induced adverse reactions including nephrotoxicity. Although different studies are available on vancomycin TDM, still there are controversies regarding the selection among different pharmacokinetic parameters including trough concentration, the area under the curve to minimum inhibitory concentration ratio (AUC24h/MIC), AUC of intervals, elimination constant, and vancomycin clearance. In this review, different pharmacokinetic parameters for vancomycin TDM have been discussed along with corresponding advantages and disadvantages. Also, vancomycin pharmacokinetic assessments are discussed in patients with altered pharmacokinetic parameters including those with renal and/or hepatic failure, critically ill patients, patients with burn injuries, intravenous drug users, obese and morbidly obese patients, those with cancer, patients undergoing organ transplantation, and vancomycin administration during pregnancy and lactation. An individualized dosing regimen is required to guarantee the optimum therapeutic responses and minimize adverse reactions including acute kidney injury in these special groups of patients. According to the pharmacoeconomic data on vancomycin TDM, pharmacokinetic assessments would be cost-effective in patients with altered pharmacokinetics and are associated with shorter hospitalization period, faster clinical stability status, and shorter courses of inpatient vancomycin administration.

Isavuconazole Pharmacokinetics and Pharmacodynamics in Children

Isavuconazole is a broad-spectrum azole anti-fungal not yet approved in children. We conducted a retrospective, single-center review of isavuconazole use and routine therapeutic drug monitoring in pediatric patients, extracting demographic, dosing, concentration, mortality and hepatoxicity data. We constructed a nonparametric population model using Pmetrics. Of 26 patients, 19 (73%) were male. The mean (SD) age and weight were 12.7 (5.5) years and 50.9 (26.8) kg. Eighty percent received between 9.7 and 10.6 mg/kg per dose. Ten (38%) subjects had proven fungal disease and eight (31%) had probable disease, mostly with Candida and Aspergillus spp. The predicted steady-state isavuconazole concentrations in our patients were similar to previous reports in children and adults, and simulations with the proposed dosing of 10 mg/kg/dose every 8 h for 2 days followed by once daily maintenance matched effective adult exposures. Attributable mortality (5 of 11 deaths) was associated with steady-state daily AUC < 60 mg∗h/L and higher AST/ALT with trough concentrations > 5 mg/L. Neither dose nor trough alone correlated well with AUC, but AUC can be estimated with one sample 10 h after the first maintenance dose or a trough concentration, if combined with a Bayesian approach or a peak and trough without a Bayesian approach.

[Performance evaluation of a precision dosing service for vancomycin in a tertiary level pediatric hospital]

Background

Plasma level-based therapeutic drug monitoring of vancomycin is recommended in the treatment of complex pediatric infections in order to increase the probability of achieving safe and effective pharmacotherapy.

Objective

To retrospectively evaluate the activities and performance of pharmacotherapeutic optimization based on vancomycin levels at a tertiary pediatric hospital between 2007 and 2020.

Métodos

Vancomycin levels of pediatric patients were analyzed, assessing care quality indicators and analytical verifications, as well as aspects related to teaching and research. The predictive performance of vancomycin levels was evaluated after adjustment of the therapeutic regimen using a population pharmacokinetic optimization program (BestDose v1.126) considering the coefficient of determination (R2), the mean absolute percentage error (MAPE), and the root mean square error (RMSE).

Results

13269 vancomycin level determinations were analyzed; 70% were trough levels and 81% belonged to patients in the intensive care units. Forty percent of the trough levels were within the therapeutic range when adjusted without software. Three hundred seventy-four pharmacotherapeutic interventions, of which 97% were accepted by the treating physician; 75% of the post-adjustment trough levels were within the therapeutic range, compared to 40% when the approach was empirical, a difference that was statistically significant (p=0.03). The values associated with predictive performance (n subgroup of patients = 91) were: R2=0.61, MAPE=28.16%, and RMSE=3.3, which all showed to be adequate.

Conclusion

The performance of therapeutic vancomycin monitoring and related pharmacokinetic clinical activities showed to be good.

Bayesian method application: Integrating mathematical modeling into clinical pharmacy through vancomycin therapeutic monitoring

The most recent consensus guidelines for dosing and monitoring vancomycin recommended the use of area-under-the-curve with Bayesian estimation for therapeutic monitoring. As this is a modern concept in the practice of clinical pharmacy, the main objective of this review is to introduce the fundamentals of Bayesian estimation and its mathematical application as it relates to vancomycin therapeutic drug monitoring. In addition, we aim to identify pharmacokinetic (PK) software programs that incorporate Bayesian estimation for vancomycin dosing and to describe the PK models utilized in those software programs for the adult population. Twelve software programs that utilize Bayesian estimation were identified, which included: Adult and Pediatric Kinetics, Best Dose, ClinCalc, DoseMeRx, ID-ODS, InsightRx, MwPharm++, NextDose, PrecisePK, TDMx, Tucuxi, and VancoCalc. The software programs varied in the population PK models used as the Bayesian a priori. With the presence of various vancomycin Bayesian software programs, it is important to choose those that utilize PK models reflective of the specific patient population.

Bibliometric and visual analysis of nephrotoxicity research worldwide

Background: Nephrotoxicity of drugs contributes to acute kidney injury with high mortality and morbidity, which crucially limits the application and development of drugs. Although many publications on nephrotoxicity have been conducted globally, there needs to be a scientometric study to systematically analyze the intellectual landscape and frontiers research trends in the future.

Methods: Publications on nephrotoxicity from 2011 to 2021 were collected to perform bibliometric visualization using VOSviewer, CiteSpace, and Scimago Graphica software based on the Web of Science Core Collection.

Results: A total of 9,342 documents were analyzed, which were primarily published in the United States (1,861), China (1,724), and Egypt (701). For institutions, King Saud University (166) had the most publications; Food and Chemical Toxicology, PLOS One, and Antimicrobial Agents and Chemotherapy were productive journals, primarily concentrating on the mechanisms of nephrotoxicity and renoprotective in cisplatin and antibiotics, especially in oxidative stress. Burst detection suggested that cisplatin, piperacillin-tazobactam, vancomycin-induced nephrotoxicity, antioxidants, and new biomaterials are frontiers of research.

Conclusion: This study first provides an updated perspective on nephrotoxicity and renoprotective strategies and mechanisms. This perspective may benefit researchers in choosing suitable journals and collaborators and assisting them in the deep understanding of the nephrotoxicity and renoprotective hotspots and frontiers.

Systematic Evaluation of Voriconazole Pharmacokinetic Models without Pharmacogenetic Information for Bayesian Forecasting in Critically Ill Patients

Voriconazole (VRC) is used as first line antifungal agent against invasive aspergillosis. Model-based approaches might optimize VRC therapy. This study aimed to investigate the predictive performance of pharmacokinetic models of VRC without pharmacogenetic information for their suitability for model-informed precision dosing. Seven PopPK models were selected from a systematic literature review. A total of 66 measured VRC plasma concentrations from 33 critically ill patients was employed for analysis. The second measurement per patient was used to calculate relative Bias (rBias), mean error (ME), relative root mean squared error (rRMSE) and mean absolute error (MAE) (i) only based on patient characteristics and dosing history (a priori) and (ii) integrating the first measured concentration to predict the second concentration (Bayesian forecasting). The a priori rBias/ME and rRMSE/MAE varied substantially between the models, ranging from −15.4 to 124.6%/−0.70 to 8.01 mg/L and from 89.3 to 139.1%/1.45 to 8.11 mg/L, respectively. The integration of the first TDM sample improved the predictive performance of all models, with the model by Chen (85.0%) showing the best predictive performance (rRMSE: 85.0%; rBias: 4.0%). Our study revealed a certain degree of imprecision for all investigated models, so their sole use is not recommendable. Models with a higher performance would be necessary for clinical use.

Vancomycin area under the curve versus trough only guided dosing and the risk of acute kidney injury: Systematic review and meta-analysis

Vancomycin is commonly used to treat methicillin-resistant Staphylococcus aureus infections and is known to cause nephrotoxicity. Previous Vancomycin Consensus Guidelines recommended targeting trough concentrations but the 2020 Guidelines suggest monitoring vancomycin area under the curve (AUC) given the reduced risk of acute kidney injury (AKI) at similar levels of efficacy. This meta-analysis compares vancomycin-induced AKI incidence using AUC-guided dosing strategies versus trough-based monitoring. Literature was queried from Medline (Ovid), Web of Science, and Google Scholar from database inception through November 5, 2021. Interventional or observational studies reporting the incidence of vancomycin-induced AKI between AUC- and trough-guided dosing strategies were included. In the primary analysis, the Vancomycin Consensus Guidelines definition for AKI was used if reported; otherwise, the Risk, Injury, and Failure; and Loss, and End-stage kidney disease (RIFLE) or Kidney Disease Improving Global Outcomes (KDIGO) definitions were used. The incidence of nephrotoxicity was evaluated between the two strategies using a Mantel-Haenszel random-effects model, and odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Subgroup analyses for adjusted ORs and AKI definitions were performed. Heterogeneity was identified using Cochrane's Q test and I² statistics. A total of 10 studies with 4231 patients were included. AUC-guided dosing strategies were associated with significantly less vancomycin-induced AKI than trough-guided strategies [OR 0.625, 95% CI (0.469-0.834), p = 0.001; I²  = 25.476]. A subgroup analysis of three studies reporting adjusted ORs yielded similar results [OR 0.475, 95% CI (0.261-0.863), p = 0.015]. Stratification by AKI definition showed a significant reduction in AKI with the Vancomycin Consensus Guidelines definition [OR 0.552, 95% CI (0.341-0.894), p = 0.016] but failed to find significance in the alternative definitions. Area under the curve-guided dosing strategies are associated with a lower incidence of vancomycin-induced AKI versus trough-guided dosing strategies (GRADE, low). Limitations included the variety of AKI definitions and the potential for confounding bias.