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

Applications of model simulation in pharmacological fields and the problems of theoretical reliability

The use of mathematical models has become increasingly prevalent in pharmacological fields, particularly in drug development processes. These models are instrumental in tasks such as designing clinical trials and assessing factors like efficacy, toxicity, and clinical practice. Various types of models have been developed and documented. Nevertheless, emphasizing the reliability of parameter values is crucial, as they play a pivotal role in shaping the behavior of the system. In some instances, parameter values reported previously are treated as fixed values, which can lead to convergence towards values that deviate substantially from those found in actual biological systems. This is especially true when parameter values are determined through fitting to limited observations. To mitigate this risk, the reuse of parameter values from previous reports should be approached with a critical evaluation of their validity. Currently, there is a proposal for a simultaneous search for plausible values for all parameters using comprehensive search algorithms in both pharmacokinetic and pharmacodynamic or systems pharmacological models. Implementing these methodologies can help address issues related to parameter determination. Furthermore, integrating these approaches with methods developed in the field of machine-learning field has the potential to enhance the reliability of parameter values and the resulting model outputs.

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.

Vancomycin AUC-Based Dosing Practices in a Non-Teaching Community Hospital and Associated Outcomes: A One-Year Survey of Uniform Targets for Infections with or without MRSA

BACKGROUND

Intravenous (IV) vancomycin area under the curve (AUC)-based dosing is used uniformly for Gram-positive organisms in non-teaching community hospitals. However, evidence for using vancomycin AUC-based dosing for non-methicillin-resistant Staphylococcus aureus (non-MRSA) and less serious infections is limited in the literature. A gap in the literature also exists with respect to comparisons between the outcomes that can be derived using the regimens suggested by Bayesian programs and target doses of the AUC of 400-499 and 500-600.

METHODS

A retrospective review of all patients hospitalized in a non-teaching community hospital who used AUC-based vancomycin was performed over a 1-year period.

RESULTS

Only 17.6% of the included patients had confirmed MRSA. The values for the overall early response rate, 30-day all-cause mortality, and rate of acute kidney injury (AKI) were 50.3%, 11.3%, and 3.8%, respectively, in this population. In regression analysis, compared to non-MRSA infections, a significantly higher rate of early response was seen in patients with MRSA (unadjusted OR = 2.68, 95% CI [1.06-6.76] p = 0.04). Patients in the AUC 400-499 group had a non-significant higher incidence of 30 d mortality and new AKI compared to patients in the AUC 500-600 group. In our Kaplan-Meier survival analysis, there was no statistically significant difference between the comparison groups.

CONCLUSIONS

Early response was lower in patients with non-MRSA compared to patients with MRSA despite achieving the AUC target. There was no apparent difference in clinical outcomes between the higher and lower AUC groups. Further large-scale research is needed to confirm these findings.

Model-informed precision dosing of vancomycin for rapid achievement of target area under the concentration-time curve: A simulation study

In this study, we aimed to evaluate limited sampling strategies for achieving the therapeutic ranges of the area under the concentration-time curve (AUC) of vancomycin on the first and second day (AUC0-24 , AUC24-48 , respectively) of therapy. A virtual population of 1000 individuals was created using a population pharmacokinetic (PopPK) model, which was validated and incorporated into our model-informed precision dosing tool. The results were evaluated using six additional PopPK models selected based on a study design of prospective or retrospective data collection with sufficient concentrations. Bayesian forecasting was performed to evaluate the probability of achieving the therapeutic range of AUC, defined as a ratio of estimated/reference AUC within 0.8-1.2. The Bayesian posterior probability of achieving the AUC24-48 range increased from 51.3% (a priori probability) to 77.5% after using two-point sampling at the trough and peak on the first day. Sampling on the first day also yielded a higher Bayesian posterior probability (86.1%) of achieving the AUC0-24 range compared to the a priori probability of 60.1%. The Bayesian posterior probability of achieving the AUC at steady-state (AUCSS ) range by sampling on the first or second day decreased with decreased kidney function. We demonstrated that second-day trough and peak sampling provided accurate AUC24-48 , and first-day sampling may assist in rapidly achieving therapeutic AUC24-48 , although the AUCSS should be re-estimated in patients with reduced kidney function owing to its unreliable predictive performance.

Use of a common spreadsheet program to demonstrate the ability of Bayesian forecasting to estimate the pharmacokinetic parameters of antibiotics

OBJECTIVES

Recent guidelines for vancomycin have incorporated the use of Bayesian forecasting, reinforcing the need to inform students in pharmacy and clinical pharmacology of its use in therapeutic drug monitoring. The goal was to devise a PharmD research project that could demonstrate to students through simulation and data generation the utility of the Bayesian approach in estimating the pharmacokinetics of gentamicin and vancomycin.

METHODS

A series of steps were devised using Microsoft Excel to simulate patient data based on study-derived means and variances, pharmacokinetic modelling, random selection of sparse blood samples, introduce random error into the selected concentrations based on assay variability measure, and finally, inputting of the information into an add-in computer program to find the pharmacokinetic estimates using Bayesian forecasting.

KEY FINDINGS

Excellent correlations were seen between Bayesian estimates and true clearances. Lower assay variability tended to provide better estimates than larger assay variability for gentamicin, and for vancomycin, selecting a sample during the distribution phase and near the trough values tended to provide estimates with less bias and greater precision.

CONCLUSIONS

The approach used was able to demonstrate all aspects involved in Bayesian forecasting, and the results supported its use for these antibiotics.

Association between vancomycin therapeutic drug monitoring and clinical outcomes in treating neonatal sepsis

BACKGROUND

Neonatal sepsis is commonly treated with vancomycin in the neonatal intensive care unit. Therapeutic drug monitoring of vancomycin is routinely used to personalise dosing to optimise effectiveness and avoid toxicity.

OBJECTIVES

This study aimed to define a target range by evaluating associations between vancomycin trough concentrations or area under the concentration time curve over 24 hours (AUC24h) and clinical outcomes in neonates.

METHODS

Neonates, who were admitted to the neonatal intensive care unit and received intravenous vancomycin, were included in this retrospective cohort study. For evaluating effectiveness, patients who received vancomycin for < 5 days were excluded. The AUC24h was estimated based on a study-derived population pharmacokinetic model. Primary outcomes were persistent/recurrent infections and mortality within 30 days. Secondary outcomes, including acute kidney injury (AKI), were also assessed. Logistic regression and classification and regression tree analyses were performed.

RESULTS

A total of 448 patients (123 patients for effectiveness analysis) were included. A vancomycin trough > 10 mg/L was associated with 70% lower odds of persistent/recurrent infections (adjusted OR 0.30, 95% CI 0.09-0.86; P = 0.023). Patients who took more than a day to reach target range had 1.4 times higher odds of persistent/recurrent infections or death (P = 0.04). A vancomycin trough > 15 mg/L was associated with a three times higher risk of AKI (P = 0.003). An AUC24h of 420-650 mg*h/L was also associated with the lowest risk of composite outcomes (adjusted OR 0.29, 95% CI 0.08-0.86; P = 0.025).

CONCLUSION

A vancomycin trough target range of 10-15 mg/L and achievement of this target within a day of treatment initiation were associated with the most optimal clinical outcomes in treating neonatal sepsis.

The Use of Levothyroxine Absorption Tests in Clinical Practice

Although levothyroxine (LT4) is a widely prescribed drug, more than 30% of LT4-treated patients fail to achieve the recommended serum level of thyrotropin with a body weight-based dose of LT4. An LT4 absorption test (LT4AT) is part of the workup for confirming normal LT4 absorption or diagnosing malabsorption. We searched PubMed with the terms levothyrox*, L-T4, LT4, TT4, FT4, FT3, TT3, test, loading, uptake, absorp*, "absorb*, bioavailab*, bioequiv* malabsorb*, and pseudomalabsorb*. A total of 43 full-text publications were analyzed. The published procedures for LT4AT differ markedly in the test dose, formulation, test duration, frequency of blood collection, analyte (total thyroxine [TT4] or free thyroxine [FT4]), metric (absolute or relative peak or increment, or area under the curve) and the threshold for normal absorption. In a standardized LT4AT for routine use, the physician could advise the patient to not consume food, beverages, or medications the morning of the test; administer 1000 µg of LT4 in the patient's usual formulation as the test dose; ensure that the patient is supervised throughout the LT4AT; perform a 4-hour test, with hourly blood samples; assay FT4; and consider that normal LT4 absorption corresponds to an FT4 increment of more than 0.40 ng/dL (5.14 pmol/L) or a TT4 increment of more than 6 μg/dL (77.23 nmol/L) for a test dose of at least 300 µg, or a percentage TT4 absorption of more than 60%. If the test indicates abnormal LT4 absorption, the physician can increase the LT4 dose, change the formulation or administration route, and/or refer the patient to a gastroenterologist.

Transdermal patches based on chitosan/hydroxypropyl methylcellulose and polyvinylpyrrolidone/hydroxypropyl methylcellulose polymer blends for gentamycin administration

Biofilm-forming bacteria have sent alarms to the world about the emerging of bacterial resistance. Gentamycin is an aminoglycoside broad-spectrum antibiotic used against microbial infections. The transdermal drug delivery method is a major system used to reduce drug toxicity and avoid first-pass metabolism. Gentamycin was formulated in a transdermal polymeric formula using hydroxypropyl methylcellulose (HPMC), polyvinylpyrrolidone (PVP), and Chitosan in the presence of palmitic acid as a permeation enhancer. In this research, gentamycin extended drug release behavior was successfully done in different polymeric formulas containing (HPMC/PVP) and (HPMC/Chitosan), with a maximum drug release of <70%. In addition, drug diffusion was found to be dependent on the rate of drug release. The controlled release formulas selected for antimicrobial assay show that HPMC/Chitosan formulas have successfully inhibited microbial and biofilm growth by 90%. In conclusion, gentamycin can be formulated in a transdermal polymeric film to target skin infection, reduce drug side effects and avoid drug first-pass metabolism.

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.

Impact of Pharmacist-Led Multidisciplinary Team to Attain Targeted Vancomycin Area under the Curved Monitoring in a Tertiary Care Center in Thailand

Vancomycin Area Under the Curve (AUC) monitoring has been recommended to ensure successful clinical outcomes and minimize the risk of nephrotoxicity, rather than traditional trough concentration. However, vancomycin AUC monitoring by a pharmacist-led multidisciplinary team (PMT) has not been well established in Southeast Asia. This study was conducted at Thammasat University Hospital. Adult patients aged ≥ 18 years who were admitted and received intravenous vancomycin ≥48 h were included. The pre-PMT period (April 2020-September 2020) was defined as a period using traditional trough concentration, while the post-PMT period (October 2020-March 2021) was defined as a period using PMT to monitor vancomycin AUC. The primary outcome was the rate of achievement of the therapeutic target of an AUC/MIC ratio of 400-600. There was a significantly higher rate of achievement of therapeutic target vancomycin AUC during post-PMT period (66.7% vs. 34.3%, p < 0.001). Furthermore, there was a significant improvement in the clinical cure rate (92.4% vs. 69.5%, p < 0.001) and reduction in 30-day ID mortality (2.9% vs. 12.4%, p = 0.017) during the post-PMT period. Our study demonstrates that PMT was effective to help attain a targeted vancomycin AUC, improve the clinical cure rate, and reduce 30-day ID mortality. This intervention should be encouraged to be implemented in Southeast Asia.

Systematic review of efficacy, safety and pharmacokinetics of intravenous and intraventricular vancomycin for central nervous system infections

Objective: The decision of vancomycin dosage for central nervous system (CNS) infections is still a challenge because its bactericidal nature in cerebrospinal fluid (CSF) has not been confirmed by human studies. This study systematically reviewed the literatures on vancomycin in patients with meningitis, ventriculitis, and CNS device-associated infections, to assess efficacy, safety, and pharmacokinetics to better serve as a practical reference.

Methods: Medline, Embase, and Cochrane Library were searched using terms vancomycin, Glycopeptides, meningitis, and central nervous system infections. Data were extracted including characteristics of participants, causative organism(s), administration, dosage, etc., The clinical response, microbiological response, adverse events and pharmacokinetic parameters were analyzed.

Results: Nineteen articles were included. Indications for vancomycin included meningitis, ventriculitis, and intracranial device infections. No serious adverse effects of intravenous (IV) and intraventricular (IVT) vancomycin have been reported. Dosages of IV and IVT vancomycin ranged from 1000–3000 mg/day and 2–20 mg/day. Duration of IV and IVT vancomycin therapy most commonly ranged from 3–27 days and 2–21 days. Therapeutic drug monitoring was conducted in 14 studies. Vancomycin levels in CSF in patients using IV and IVT vancomycin were varied widely from 0.06 to 22.3 mg/L and 2.5–292.9 mg/L. No clear relationships were found between vancomycin CSF levels and efficacy or toxicity.

Conclusion: Using vancomycin to treat CNS infections appears effective and safe based on current evidence. However, the optimal regimens are still unclear. Higher quality clinical trials are required to explore the vancomycin disposition within CNS.

Vancomycin Area under the Concentration-Time Curve Estimation Using Bayesian Modeling versus First-Order Pharmacokinetic Equations: A Quasi-Experimental Study

Aim: To evaluate the efficiency of Bayesian modeling software and first-order pharmacokinetic (PK) equations to calculate vancomycin area under the concentration-time curve (AUC) estimations. Methods: Unblinded, crossover, quasi-experimental study at a tertiary care hospital for patients receiving intravenous vancomycin. Vancomycin AUC monitoring was compared using Bayesian modeling software or first-order PK equations. The primary endpoint was the time taken to estimate the AUC and determine regimen adjustments. Secondary endpoints included the percentage of vancomycin concentrations usable for AUC calculations and acute kidney injury (AKI). Results: Of the 124 patients screened, 34 patients had usable vancomycin concentrations that led to 44 AUC estimations. Without electronic health record (EHR) integration, the time from assessment to intervention in the Bayesian modeling platform was a median of 9.3 min (quartiles Q₁–Q₃ 7.8–12.4) compared to 6.8 min (Q₁–Q₃ 4.8–8.0) in the PK equations group (p = 0.004). With simulated Bayesian software integration into the EHR, however, the median time was 3.8 min (Q₁–Q₃ 2.3–6.9, p = 0.019). Vancomycin concentrations were usable in 88.2% in the Bayesian group compared to 48.3% in the PK equation group and there were no cases of AKI. Conclusion: Without EHR integration, Bayesian software was more time-consuming to assess vancomycin dosing than PK equations. With simulated integration, however, Bayesian software was more time efficient. In addition, vancomycin concentrations were more likely to be usable for calculations in the Bayesian group.