Evaluation of target area under the concentration-time curve of vancomycin in an initial dosing design: a retrospective cohort study

OBJECTIVES

Area under the concentration-time curve (AUC)-guided dosing of vancomycin was introduced in a clinical setting; however, the target range of non-steady-state AUCs, such as Day 1 AUC and Day 2 AUC, remains controversial. Therefore, we sought to determine pharmacokinetic parameter thresholds and identify independent risk factors associated with acute kidney injury (AKI) to establish a safe initial dosing design for vancomycin administration.

METHODS

A single-centre, retrospective, cohort study of hospitalized patients treated with vancomycin was conducted to determine the threshold of both non-steady-state AUCs (Day 1 and 2 AUCs) and trough levels at the first blood sampling point (therapeutic drug monitoring, TDM). In addition, independent risk factors associated with AKI were evaluated using univariate and multivariate logistic regression analyses.

RESULTS

The thresholds for predicting AKI were estimated as 456.6 mg·h/L for AUC0-24h, 554.8 mg·h/L for AUC24-48h, 1080.8 mg·h/L for AUC0-48h and 14.0 μg/mL for measured trough levels, respectively. In a multivariate analysis, Day 2 AUC ≥ 554.8 mg·h/L [adjusted odds ratio (OR), 57.16; 95% confidence interval (CI), 11.95-504.05], piperacillin/tazobactam (adjusted OR, 15.84; 95% CI, 2.73-127.70) and diuretics (adjusted OR, 4.72; 95% CI, 1.13-21.01) were identified as risk factors for AKI.

CONCLUSIONS

We identified thresholds for both AUCs in the non-steady-state and trough levels at the first TDM. Our results highlight the importance of monitoring not only the AUC but also trough levels during vancomycin treatment to reduce the likelihood of AKI.

Population pharmacokinetics of vancomycin in patients with diabetic foot infection: a comparison of five models

Purpose

This study aimed to compare individual pharmacokinetic (PK) parameters of vancomycin with predicted values from five population PK models in patients with diabetic foot infections (DFIs).

Methods

Patients with a diagnosis of DFI and an estimated glomerular filtration rate (eGFR) ≥ 30 mL/min were included in the study. Individual PK data was carried on by collecting three vancomycin serum concentrations in a steady-state condition. Five published population-based nomograms were assumed to predict PK parameters. Optimal vancomycin exposure was considered as a trough level of 15-20 mg/L or the area under the curve over 24 h/minimum inhibitory concentration (AUC24/MIC) ≥ 400.

Results

A total of 48 samples from 16 patients were analyzed. There was a statistically significant difference between the volume of distribution (Vd) obtained from population methods and the individual estimations (P ≤ 0.001 in Ambrose and Burton, P = 0.010 and 0.006 in Bauer and Burton revised models, respectively). AUC/MIC ≥ 400 was achieved in 68.7% of patients while 50% had a trough level of less than 15 mg/L.

Conclusions

Vancomycin PK parameters, particularly individualized Vd, may not be predictable by population nomograms in patients with DFI and stable renal function. Moreover, the weak correlation between AUC24 values and trough concentrations underlines the starting practice of vancomycin AUC24-based monitoring and dosing in the clinical setting.

Falsely decreased vancomycin caused by rheumatoid factor: A case report

BACKGROUND

Vancomycin is associated with potential nephrotoxicity and trough concentrations need to be monitored in certain patients. Falsely decreased vancomycin measurement may result in overtreatment and need to be identified promptly by clinicians and pharmacists to avoid toxicities.

METHODS AND RESULTS

We report a case of rheumatoid factor-mediated falsely low vancomycin measurement with Abbott particle-enhanced turbidimetric inhibition immunoassay (PETINIA) method. Reanalyzing the sample using an alternative method, removing the interferences using heterophile blocking reagent as well as rheumatoid factor clean-up solution all helped to solve the false results. Results from alternative method and interference studies showed vancomycin concentrations reached toxic concentrations in the patient and administration of the drug was immediately terminated. The patient experienced a transient increase in serum creatinine.

CONCLUSIONS

Even though most modern immunoassays use blocking agents to neutralize interfering antibodies such as rheumatoid factor, it is important for health care professionals to understand that occasional interference still occurs due to the heterogeneous nature of rheumatoid factor.

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.

Application of Machine Learning Classification to Improve the Performance of Vancomycin Therapeutic Drug Monitoring

Bayesian therapeutic drug monitoring (TDM) software uses a reported pharmacokinetic (PK) model as prior information. Since its estimation is based on the Bayesian method, the estimation performance of TDM software can be improved using a PK model with characteristics similar to those of a patient. Therefore, we aimed to develop a classifier using machine learning (ML) to select a more suitable vancomycin PK model for TDM in a patient. In our study, nine vancomycin PK studies were selected, and a classifier was created to choose suitable models among them for patients. The classifier was trained using 900,000 virtual patients, and its performance was evaluated using 9000 and 4000 virtual patients for internal and external validation, respectively. The accuracy of the classifier ranged from 20.8% to 71.6% in the simulation scenarios. TDM using the ML classifier showed stable results compared with that using single models without the ML classifier. Based on these results, we have discussed further development of TDM using ML. In conclusion, we developed and evaluated a new method for selecting a PK model for TDM using ML. With more information, such as on additional PK model reporting and ML model improvement, this method can be further enhanced.

Diagnostic Value of Multiple Serum Biomarkers for Vancomycin-Induced Kidney Injury

Acute kidney injury (AKI) is a major contributor to in-hospital morbidity and mortality. Vancomycin, one of the most commonly used antibiotics in a clinical setting, is associated with AKI, with its incidence ranging up to 43%. Despite the high demand, few studies have investigated serum biomarkers to detect vancomycin-induced kidney injury (VIKI). Here, we evaluated the diagnostic value of nine candidate serum biomarkers for VIKI. A total of 23,182 cases referred for vancomycin concentration measurement from January 2018 to December 2019 were screened and 28 subjects with confirmed VIKI were enrolled (VIKI group). Age- and sex- matched control group consisted of 21 subjects who underwent vancomycin therapy without developing VIKI (non-VIKI group), and 23 healthy controls (HC group). The serum concentrations of clusterin, retinol binding protein 4 (RBP4), interleukin-18 (IL-18), tumor necrosis factor receptor 1 (TNF-R1), C-X-C motif chemokine ligand 10 (CXCL10), neutrophil gelatinase-associated lipocalin (NGAL), osteopontin, trefoil factor-3 (TFF3), and cystatin C were compared among the three groups, and their correlations with estimated glomerular filtration rate (eGFR) and diagnostic values for VIKI were assessed. All of the biomarkers except clusterin and RBP4 exhibited significant elevation in the VIKI group. Serum TFF3, cystatin C, TNF-R1, and osteopontin demonstrated an excellent diagnostic value for VIKI (TFF3, area under the curve (AUC) 0.932; cystatin C, AUC 0.917; TNF-R1, AUC 0.866; osteopontin, AUC 0.787); and except osteopontin, a strong negative correlation with eGFR (TFF3, r = −0.71; cystatin C, r = −0.70; TNF-R1, r = −0.60). IL-18, CXCL10, and NGAL showed weak correlation with eGFR and moderate diagnostic value for VIKI. This study tested multiple serum biomarkers for VIKI and showed that serum TFF3, cystatin C, TNF-R1, and osteopontin could efficiently discriminate VIKI patients. Further studies are warranted to clarify the diagnostic value of these biomarkers in VIKI.

Vancomycin Advanced Therapeutic Drug Monitoring: Exercise in Futility or Virtuous Endeavor to Improve Drug Efficacy and Safety?

Vancomycin is commonly prescribed to hospitalized patients. Decades of pharmacokinetic/pharmacodynamic research culminated in recommendations to monitor the ratio of the area under the concentration-time curve (AUC) to the minimum inhibitory concentration in order to optimize vancomycin exposure and minimize toxicity in the revised 2020 guidelines. These guideline recommendations are based on limited data without high-quality evidence and limitations in strength. Despite considerable effort placed on vancomycin therapeutic drug monitoring (TDM), clinicians should recognize that the majority of vancomycin use is empiric. Most patients prescribed empiric vancomycin do not require it beyond a few days. For these patients, AUC determinations during the initial days of vancomycin exposure are futile. This added workload may detract from high-level patient care activities. Loading doses likely achieve AUC targets, so AUC monitoring after a loading dose is largely unnecessary for broad application. The excessive vancomycin TDM for decades has been propagated with limitations in evidence, and it should raise caution on contemporary vancomycin TDM recommendations.

Contrasting effects of linezolid on healthy and dysfunctional human neutrophils: reducing C5a-induced injury

Methicillin-resistant Staphylococcus aureus (MRSA) is an important cause of ventilator-associated pneumonia (VAP). Patients with VAP have poorly functioning neutrophils, related to increased levels of the complement fragment C5a. The antibiotic linezolid has been useful in controlling MRSA-related VAP infections; however clinical benefit does not always correlate with antimicrobial effect, suggesting the possibility of immunomodulatory properties. Here the effects of linezolid on healthy and dysfunctional neutrophils (modelled by C5a-induced injury) was investigated. Functional assays (killing, phagocytosis, transmigration, and respiratory burst) were used to assess the effects of pre-, co- and post-incubating linezolid (0.4-40 mg/L) with healthy neutrophils relative to those with C5a-induced injury. C5a decreased neutrophil killing, and phagocytosis of MRSA. Furthermore, C5a significantly decreased neutrophil transmigration to IL-8, but did not affect respiratory burst. Co-incubation of linezolid significantly improved killing of MRSA by dysfunctional neutrophils, which was supported by concomitant increases in phagocytosis. Conversely linezolid impaired killing responses in healthy neutrophils. Pre- or post-incubation of linezolid prior or following C5a induced injury had no effect on neutrophil function. This study suggests that linezolid has immunomodulatory properties that protect human neutrophils from injury and provides insight into its mode of action beyond a basic antibiotic.

Multi-Drug-Resistant Organisms in Burn Infections

Background: Infection is the most frequent complication after severe burns and remains the predominant cause of death. Burn patients may require multiple courses of antibiotics, lengthy hospitalizations, and invasive procedures that place burn patients at especially high risk for infections with multi-drug-resistant organisms (MDROs). Methods: The published literature on MDROs in burn patients was reviewed to develop a strategy for managing these infections. Results: Within a burn unit meticulous infection prevention and control measures and effective antimicrobial stewardship can limit MDRO propagation and decrease the antibiotic pressure driving the selection of MDROs from less resistant strains. Several new antimicrobial agents have been developed offering potential therapeutic options, but familiarity with their benefits and limitations is required for safe utilization. Successful management of MDRO burn infections is supported by a multifactorial approach. Novel non-antibiotic therapeutics may help combat MDRO infections and outbreaks. Conclusions: Multi-drug-resistant organisms are being identified with increasing frequency in burn patients. Effective sensitivity testing is essential to identify MDROs and to direct appropriate antibiotic choices for patient treatment.

Vancomycin-Induced Kidney Injury: Animal Models of Toxicodynamics, Mechanisms of Injury, Human Translation, and Potential Strategies for Prevention

Vancomycin is a recommended therapy in multiple national guidelines. Despite the common use, there is a poor understanding of the mechanistic drivers and potential modifiers of vancomycin-mediated kidney injury. In this review, historic and contemporary rates of vancomycin-induced kidney injury (VIKI) are described, and toxicodynamic models and mechanisms of toxicity from preclinical studies are reviewed. Aside from known clinical covariates that worsen VIKI, preclinical models have demonstrated that various factors impact VIKI, including dose, route of administration, and thresholds for pharmacokinetic parameters. The degree of acute kidney injury (AKI) is greatest with the intravenous route and higher doses that produce larger maximal concentrations and areas under the concentration curve. Troughs (i.e., minimum concentrations) have less of an impact. Mechanistically, preclinical studies have identified that VIKI is a result of drug accumulation in proximal tubule cells, which triggers cellular oxidative stress and apoptosis. Yet, there are several gaps in the knowledge that may represent viable targets to make vancomycin therapy less toxic. Potential strategies include prolonging infusions and lowering maximal concentrations, administration of antioxidants, administering agents that decrease cellular accumulation, and reformulating vancomycin to alter the renal clearance mechanism. Based on preclinical models and mechanisms of toxicity, we propose potential strategies to lessen VIKI.