Optimal Practice for Vancomycin Therapeutic Drug Monitoring: Position Statement From the Anti-infectives Committee of the International Association of Therapeutic Drug Monitoring and Clinical Toxicology

Vancomycin wound penetration in open-heart surgery patients receiving negative pressure wound therapy for deep sternal wound infection

INTRODUCTION

It is hypothesized that systemically administered antibiotics penetrate wound sites more effectively during negative pressure wound therapy (NPWT). However, there is a lack of clinical data from patients who receive NPWT for deep sternal wound infection (DSWI) after open-heart surgery. Here, we evaluated vancomycin penetration into exudate in this patient group.

PATIENTS AND METHODS

For this prospective observational study, we enrolled 10 consecutive patients treated with NPWT for post-sternotomy DSWI. On the first sampling day, serum and exudate samples were synchronously collected at 0 (pre-dose), 0.5, 1, 2, 3 and 6 h after vancomycin administration. On the following three consecutive days, additional samples were collected, only before vancomycin administration.

RESULTS

The ratio of average vancomycin concentration in wound exudate to in serum was higher for free (unbound) (1.51 ± 0.53) than for total (bound + unbound) (0.91 ± 0.29) concentration (p = 0.049). The percentage of free vancomycin was higher in wound exudate than serum (0.79 ± 0.19 vs. 0.46 ± 0.16; p = 0.04). Good vancomycin wound penetration was maintained on the following three days (vancomycin trough exudate-to-serum concentration ratio > 1). The total hospital stay was significantly longer in patients with DSWI (46 ± 11.6 days) versus without DSWI (14 ± 11.7 days) (p < 0.001). There was no in-hospital or 90-day mortality. Two patients experienced late DSWI recurrence. All-cause mortality was 4.8% during a median follow-up of 2.5 years.

CONCLUSION

Vancomycin effectively penetrates wound exudate in patients receiving NPWT for DSWI after open-heart surgery.The protocol for this study was registered at ClinicalTrials.gov on July 16, 2024 (NCT06506032).

Clinical validation of an innovative dried whole-blood spot method to quantify simultaneously vancomycin and creatinine in adult patients

BACKGROUND

A drawback of vancomycin use is the need for therapeutic drug monitoring and renal function monitoring. Traditional blood sampling involves drawing blood through a venepuncture. An alternative method, dried blood spot (DBS) sampling allows for self-sampling at home.

OBJECTIVES

To clinically validate a DBS method for simultaneous monitoring of vancomycin and creatinine.

METHODS

Hospitalized adults treated with intravenous vancomycin were included (trial registration NCT05257070). Blood sampling consisted of one venepuncture and one finger prick. Whole-blood DBS samples from patients were obtained by applying one drop of whole blood onto Whatman 903 filtrate paper. Bland-Altman analyses were used to assess the agreement and bias between the two measurements. Patients were asked to state their preferences for one of the two sampling methods.

RESULTS

The study involved a final analysis of 39 patient samples for the clinical validation of vancomycin and 46 patient samples for the clinical validation of creatinine. The difference between plasma and DBS concentrations was ≤20% for 77% of the vancomycin samples, the mean bias was -0.1379% (95% limit of agreement -5.899-5.623). The difference between plasma and DBS concentrations was ≤20% for 89% of the creatinine samples, the mean bias was 2.656% (95% limit of agreement -26.16-31.47). Most patients (18 out of 31) preferred a finger prick over a venepuncture and 12 patients indicated no preference.

CONCLUSIONS

This is the first study that successfully clinically validated a DBS sampling method for simultaneous measurement of vancomycin and creatinine, allowing for direct use in (outpatient) practice.

Optimizing Initial Vancomycin Dosing in Hospitalized Patients Using Machine Learning Approach for Enhanced Therapeutic Outcomes: Algorithm Development and Validation Study

BACKGROUND

Vancomycin is commonly dosed using standard weight-based methods before dose adjustments are made through therapeutic drug monitoring (TDM). However, variability in initial dosing can lead to suboptimal therapeutic outcomes. A predictive model that personalizes initial dosing based on patient-specific pharmacokinetic factors prior to administration may enhance target attainment and minimize the need for subsequent dose adjustments.

OBJECTIVE

This study aimed to develop and evaluate a machine learning (ML)-based algorithm to predict whether an initial vancomycin dose falls within the therapeutic range of the 24-hour area under the curve to minimum inhibitory concentration, thereby optimizing the initial vancomycin dosage.

METHODS

A retrospective cohort study was conducted using hospitalized patients who received intravenous vancomycin and underwent pharmacokinetic TDM consultation (n=415). The cohort was randomly divided into training and testing datasets in a 7:3 ratio, and multiple ML techniques were used to develop an algorithm for optimizing initial vancomycin dosing. The optimal algorithm, referred to as the OPTIVAN algorithm, was selected and validated using an external cohort (n=268). We evaluated the performance of 4 ML models: gradient boosting machine, random forest (RF), support vector machine (SVM), and eXtreme gradient boosting (XGB). Additionally, a web-based clinical support tool was developed to facilitate real-time vancomycin TDM application in clinical practice.

RESULTS

The SVM algorithm demonstrated the best predictive performance, achieving an area under the receiver operating characteristic curve (AUROC) of 0.832 (95% CI 0.753-0.900) for the training dataset and 0.720 (95% CI 0.654-0.783) for the external validation dataset. The gradient boosting machine followed closely with AUROC scores of 0.802 (95% CI 0.667-0.857) for the training dataset and 0.689 (95% CI 0.596-0.733) for the validation dataset. In contrast, both XGB and RF exhibited relatively lower performance. XGB achieved AUROC values of 0.769 (95% CI 0.671-0.853) for the training set and 0.707 (95% CI 0.644-0.772) for the validation set, while RF recorded AUROC scores of 0.759 (95% CI 0.656-0.846) for the test dataset and 0.693 (95% CI 0.625-0.757) for the external validation set. The SVM model incorporated 7 covariates: age, BMI, glucose, blood urea nitrogen, estimated glomerular filtration rate, hematocrit, and daily dose per body weight. Subgroup analyses demonstrated consistent performance across different patient categories, such as renal function, sex, and BMI. A web-based TDM analysis tool was developed using the OPTIVAN algorithm.

CONCLUSIONS

The OPTIVAN algorithm represents a significant advancement in personalized initial vancomycin dosing, addressing the limitations of current TDM practices. By optimizing the initial dose, this algorithm may reduce the need for subsequent dosage adjustments. The algorithm's web-based app is easy to use, making it a practical tool for clinicians. This study highlights the potential of ML to enhance the effectiveness of vancomycin treatment.

Impact of vancomycin therapeutic drug monitoring on mortality in sepsis patients across different age groups: a propensity score-matched retrospective cohort study

Background

Due to its potent antibacterial activity, vancomycin is widely used in the treatment of sepsis. Therapeutic drug monitoring (TDM) can optimize personalized vancomycin dosing regimens, enhancing therapeutic efficacy and minimizing nephrotoxic risk, thereby potentially improving patient outcomes. However, it remains uncertain whether TDM affects the mortality rate among sepsis patients or whether age plays a role in this outcome.

Methods

We analyzed data from the Medical Information Mart of Intensive Care-IV database, focusing on sepsis patients who were admitted to the intensive care unit (ICU) and treated with vancomycin. The primary variable of interest was the use of vancomycin TDM during the ICU stay. The primary outcome was 30-day mortality. To control for potential confounding factors and evaluate associations, we used Cox proportional hazards regression and propensity score matching (PSM). Subgroup and sensitivity analyses were performed to assess the robustness of our findings. Furthermore, restricted cubic spline models were utilized to investigate the relationship between age and mortality among different groups of sepsis patients, to identify potential non-linear associations.

Results

A total of 14,053 sepsis patients met the study criteria, of whom 6,826 received at least one TDM during their ICU stay. After PSM, analysis of 4,329 matched pairs revealed a significantly lower 30-day mortality in the TDM group compared with the non-TDM group (23.3% vs.27.7%, p < 0.001). Multivariable Cox proportional hazards regression showed a significantly reduced 30-day mortality risk in the TDM group [adjusted hazard ratio (HR): 0.66; 95% confidence interval (CI): 0.61-0.71; p < 0.001]. This finding was supported by PSM-adjusted analysis (adjusted HR: 0.71; 95% CI: 0.66-0.77; p < 0.001) and inverse probability of treatment weighting analysis (adjusted HR: 0.72; 95% CI: 0.67-0.77; p < 0.001). Kaplan-Meier survival curves also indicated significantly higher 30-day survival in the TDM group (log-rank test, p < 0.0001). Subgroup analyses by gender, age, and race yielded consistent results. Patients with higher severity of illness-indicated by sequential organ failure assessment scores ≥6, acute physiology score III ≥40, or requiring renal replacement therapy, vasopressors, or mechanical ventilation-experienced more pronounced mortality improvement from vancomycin TDM compared with those with lower severity scores or not requiring these interventions. The results remained robust after excluding patients with ICU stays <48 h, those with methicillin-resistant Staphylococcus aureus infections, or when considering only patients with septic shock. In subgroup analyses, patients under 65 years (adjusted HR: 0.50; 95% CI: 0.43-0.58) benefited more from vancomycin TDM than those aged 65 years and older (adjusted HR: 0.75; 95% CI: 0.67-0.83). Notably, sepsis patients aged 18-50 years had the lowest mortality rate among all age groups, at 15.2% both before and after PSM. Furthermore, in this age group, vancomycin TDM was associated with a greater reduction in 30-day mortality risk, with adjusted HRs of 0.32 (95% CI: 0.24-0.41) before PSM and 0.30 (95% CI: 0.22-0.32) after PSM.

Conclusion

Vancomycin TDM is associated with reduced 30-day mortality in sepsis patients, with the most significant benefit observed in patients aged 18-50. This age group exhibited the lowest mortality rates and experienced the greatest reduction in mortality following TDM compared with older patients.

Monitoring vancomycin blood concentrations reduces mortality risk in critically ill patients: a retrospective cohort study using the MIMIC-IV database

Background

The incidence and mortality of severe Gram-positive cocci infections are particularly high in intensive care units (ICUs). Vancomycin remains the treatment of choice for severe infections caused by Gram-positive cocci, particularly methicillin-resistant Staphylococcus aureus (MRSA). Some guidelines recommend therapeutic drug monitoring (TDM) for critically ill patients treated with vancomycin; however, there is currently a lack of evidence to support that TDM improves the mortality rates of these patients. Therefore, we designed this cohort study to compare the impact of monitoring vancomycin blood concentrations on mortality rates in critically ill patients and to provide evidence to support this routine clinical practice.

Methods

Data were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database for a retrospective cohort analysis of critically ill patients receiving intravenous vancomycin treatment. The primary outcome was the 28 day mortality rate. The propensity score matching (PSM) method was used to match the baseline characteristics between patients in the TDM group and the non-TDM group. The relationship between 28 day mortality and vancomycin TDM in the critically ill cohort was evaluated using Cox proportional hazards regression analysis and Kaplan-Meier survival curves. Validation of the primary outcomes was conducted by comparing the PSM model and the Cox proportional hazards regression model. The robustness of the conclusion was subsequently verified by subgroup and sensitivity analyses.

Results

Data for 18,056 critically ill patients who met the study criteria were collected from the MIMIC-IV database. Of these, 7,451 patients had at least one record of vancomycin blood concentration monitoring, which we defined as the TDM group. The TDM group exhibited a 28 day mortality rate of 25.7% (1,912/7,451) compared to 16.2% in the non-TDM group (1,723/10,605). After PSM, 4,264 patients were included in each of the TDM and non-TDM groups, with a 28 day mortality rate of 20.0% (1,022/4,264) in the TDM group and 26.4% (1,126/4,264) in the non-TDM group. Multivariate Cox proportional hazards analysis revealed a significantly lower 28 day mortality risk in the TDM group when compared to the non-TDM group (adjusted hazard ratio [HR]: 0.86; 95% confidence interval [CI]: 0.79, 0.93; p < 0.001). Further PSM analyses (adjusted HR: 0.91; 95% CI: 0.84, 0.99; p = 0.033) confirmed the lower risk of mortality in the TDM group. Kaplan-Meier survival analysis revealed a significantly higher survival rate at 28 days for the TDM group (log-rank test, p < 0.001). Subgroup analysis results indicated that patients with sepsis, septic shock, estimated glomerular filtration rate ≤ 60 mL/min/1.73 m2, undergoing renal replacement therapy, using vasoactive drugs, on mechanical ventilation, and those with higher severity scores (Acute Physiology Score III ≥40, Oxford Acute Severity of Illness Score ≥30, Simplified Acute Physiology Score II ≥ 30) significantly benefited from monitoring vancomycin blood concentrations. The results remained unchanged excluding patients staying in ICU for less than 48 h or those infected with MRSA.

Conclusion

This cohort study showed that monitoring vancomycin blood concentrations is associated with a significantly lower 28 day mortality rate in critically ill patients, highlighting the importance of routinely performing vancomycin TDM in these patients.

Antibiotic Use in Medical-Surgical Intensive Care Units and General Wards in Latin American Hospitals

Background

The objective of this study was to identify antibiotic stewardship (AS) opportunities in Latin American medical-surgical intensive care units (MS-ICUs) and general wards (Gral-wards).

Methods

We conducted serial cross-sectional point prevalence surveys in MS-ICUs and Gral-wards in 41 Latin American hospitals between March 2022 and February 2023. Patients >18 years of age in the units of interest were evaluated for antimicrobial use (AU) monthly (MS-ICUs) or quarterly (Gral-wards). Antimicrobial data were collected using a standardized form by the local AS teams and submitted to the coordinating team for analysis.

Results

We evaluated AU in 5780 MS-ICU and 7726 Gral-ward patients. The hospitals' median bed size (interquartile range) was 179 (125-330), and 52% were nonprofit. The aggregate AU prevalence was 53.5% in MS-ICUs and 25.5% in Gral-wards. Most (88%) antimicrobials were prescribed to treat infections, 7% for surgical prophylaxis and 5% for medical prophylaxis. Health care-associated infections led to 63% of MS-ICU and 38% of Gral-ward AU. Carbapenems, piperacillin-tazobactam, intravenous (IV) vancomycin, and ampicillin-sulbactam represented 50% of all AU to treat infections. A minority of IV vancomycin targeted therapy was associated with documented methicillin-resistant Staphylococcus aureus infection or therapeutic drug monitoring. In both units, 17% of antibiotics prescribed as targeted therapy represented de-escalation, while 24% and 15% in MS-ICUs and Gral-wards, respectively, represented an escalation of therapy. In Gral-wards, 32% of antibiotics were used without a microbiologic culture ordered. Half of surgical prophylaxis antibiotics were prescribed after the first 24 hours.

Conclusions

Based on this cohort, areas to improve AU in Latin American hospitals include antibiotic selection, de-escalation, duration of therapy, and dosing strategies.

Automated calculation and reporting of vancomycin area under the concentration-time curve: a simplified single-trough concentration-based equation approach

Vancomycin, a crucial antibiotic for Gram-positive bacterial infections, requires therapeutic drug monitoring (TDM). Contemporary guidelines advocate for AUC-based monitoring; however, using Bayesian programs for AUC estimation poses challenges. We aimed to develop and evaluate a simplified AUC estimation equation using a steady-state trough concentration (Ctrough) value. Utilizing 1,034 TDM records from 580 general hospitalized patients at a university-affiliated hospital in Ulsan, we created an equation named SSTA that calculates the AUC by applying Ctrough, body weight, and single dose as input variables. External validation included 326 records from 163 patients at a university-affiliated hospital in Seoul (EWUSH) and literature data from 20 patients at a university-affiliated hospital in Bangkok (MUSI). It was compared with other AUC estimation models based on the Ctrough, including a linear regression model (LR), a sophisticated model based on the first-order equation (VancoPK), and a Bayesian model (BSCt). Evaluation metrics, such as median absolute percentage error (MdAPE) and the percentage of observations within ±20% error (P20), were calculated. External validation using the EWUSH data set showed that SSTA, LR, VancoPK, and BSCt had MdAPE values of 6.4, 10.1, 6.6, and 7.5% and P20 values of 87.1, 82.5, 87.7, and 83.4%, respectively. External validation using the MUSI data set showed that SSTA, LR, and VancoPK had MdAPEs of 5.2, 9.4, and 7.2%, and P20 of 95, 90, and 95%, respectively. Owing to its decent AUC prediction performance, simplicity, and convenience for automated calculation and reporting, SSTA could be used as an adjunctive tool for the AUC-based TDM.

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.

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.

Is it time to recommend AUC-based vancomycin therapeutic drug monitoring only? A cross-sectional survey in China

Background

The latest published therapeutic drug monitoring (TDM) guidelines for vancomycin recommend changing trough-based monitoring to area under the concentration-to-time curve (AUC)-based monitoring. This study aimed to evaluate the implementation status and perceptions of vancomycin AUC-based TDM in China and to determine the challenges in performing AUC-based TDM.

Methods

A nationwide cross-sectional survey was conducted in China using an online questionnaire. The questionnaire comprised a total of 25 questions with open- and closed-ended answers to collect information about the current implementation of vancomycin TDM and the participants' perceptions of these practices. The questionnaire responses were collected via the Questionnaire Star platform and analyzed.

Results

A total of 161 questionnaires were completed by 131 hospitals and were included. Approximately 59.5% (78/131) of the surveyed hospitals conducted vancomycin TDM; however, only 10.7% (14/131) of these hospitals performed AUC-based vancomycin TDM. Of the eligible participants, 58.4% (94/161) had experience with vancomycin TDM, and only 37 participants (37/161, 23.0%) had the ability to estimate the AUC, primarily through Bayesian simulation (33/161, 20.5%). The participants considered the following challenges to implementing AUC-based monitoring: (1) the high cost of AUC-based monitoring; (2) inadequate knowledge among pharmacists and/or physicians; (3) the complexity of AUC calculations; (4) difficulty obtaining AUC software; and (5) unclear benefit of AUC-based monitoring.

Conclusion

The majority of surveyed hospitals have not yet implemented AUC-based vancomycin TDM. Multiple challenges should be addressed before wide implementation of AUC-based monitoring, and guidance for trough-based monitoring is still needed.

Effects of lung inflammation and injury on pulmonary tissue penetration of meropenem and vancomycin in a model of unilateral lung injury

OBJECTIVE

The timing and dosing of antimicrobial therapy are key in the treatment of pneumonia in critically ill patients. It is uncertain whether the presence of lung inflammation and injury affects tissue penetration of intravenously administered antimicrobial drugs. The effects of lung inflammation and injury on tissue penetration of two antimicrobial drugs commonly used for pneumonia were determined in an established model of unilateral lung injury.

METHODS

Unilateral lung injury was induced in the left lung of 13 healthy pigs through cyclic rinsing; the right healthy lung served as control. Infusions of meropenem and vancomycin were administered and concentrations of these drugs in lung tissue, blood, and epithelial lining fluid (ELF) were compared over a period of 6 h.

RESULTS

Median vancomycin lung tissue concentrations and penetration ratio were higher in inflamed and injured lungs compared with uninflamed and uninjured lungs (AUC0-6h: P = 0.003 and AUCdialysate/AUCplasma ratio: P = 0.003), resulting in higher AUC0-24/MIC. Median meropenem lung tissue concentrations and penetration ratio in inflamed and injured lungs did not differ from that in uninflamed and uninjured lungs (AUC0-6: P = 0.094 and AUCdialysate/AUCplasma ratio: P = 0.173). The penetration ratio for both vancomycin and meropenem into ELF was similar in injured and uninjured lungs.

CONCLUSION

Vancomycin penetration into lung tissue is enhanced by acute inflammation and injury, a phenomenon barely evident with meropenem. Therefore, inflammation in lung tissue influences the penetration into interstitial lung tissue, depending on the chosen antimicrobial drug. Measurement of ELF levels alone might not identify the impact of inflammation and injury.

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.

The Impact of Augmented Renal Clearance on Vancomycin Pharmacokinetics and Pharmacodynamics in Critically Ill Patients

Augmented renal clearance (ARC), defined as a creatinine clearance (CrCl) > 130 mL/min/1.73 m2, is observed in 30-65% of critically ill patients. When following standard dosage guidelines, patients with ARC often experience subtherapeutic vancomycin levels, resulting in treatment failure due to accelerated drug elimination. This review aims to explore ARC's impact on vancomycin pharmacokinetics and pharmacodynamics (PK/PD) indices in ARC patients, seeking to identify an accurate dose adjustment method for this patient population. In September 2023, a comprehensive literature search was conducted on the MEDLINE and EMBASE databases to include all available studies providing information on the impact of ARC on vancomycin therapy in critically ill adults. Articles that studied the pediatric population and those with insufficient PK data were excluded. A total of 21 articles met the inclusion criteria. The findings revealed a positive correlation between CrCl and vancomycin clearance, indicating low serum concentrations. Therefore, upward dosing adjustments are necessary to improve treatment success. Younger age consistently emerged as a major contributor to ARC and vancomycin PK/PD alterations. This study summarizes the PK/PD alterations, current dosage recommendations and proposes preliminary recommendations on possible dosing approaches to decrease the risk of subtherapeutic exposure in this patient population.

Dose optimization and target attainment of vancomycin in children

Vancomycin is a glycopeptide antibiotic that has been adopted in clinical practice to treat gram-positive infections for more than 70 years. Despite vancomycin's long history of therapeutic use, optimal dose adjustments and pharmacokinetic/pharmacodynamic (PK/PD) target attainment in children are still under debate. Therapeutic drug monitoring (TDM) has been widely integrated into pediatric clinical practice to maximize efficacy and safety of vancomycin treatment. Area under the curve (AUC)-guided TDM has been recently recommended instead of trough-only TDM to ensure PK/PD target attainment of AUC0-24h/minimal inhibitory concentration (MIC) > 400 to 600 and minimize acute kidney injury risk. Bayesian forecasting in pediatric patients allows estimation of population PK to accurately predict individual vancomycin concentrations over time, and consequently total vancomycin exposure. AUC-guided TDM for vancomycin, preferably with Bayesian forecasting, is therefore suggested for all pediatric age groups and special pediatric populations. In this review we aim to analyze the current literature on the pediatric use of vancomycin and summarize the current knowledge on dosing optimization for target attainment in special patient populations.

Risk of Acute Kidney Injury Based on Vancomycin Target Trough Attainment Strategy: Area-Under-the-Curve-Guided Bayesian Software, Nomogram, or Trough-Guided Dosing

BACKGROUND

Guidelines support area-under-the-curve (AUC) monitoring for vancomycin dosing which may lower overall doses and reduce acute kidney injury (AKI).

OBJECTIVE

The aim of this study was to compare incidence of AKI across 3 vancomycin dosing modalities: AUC-targeted Bayesian pharmacokinetic software, AUC-targeted empiric dosing nomogram, and trough-guided dosing using clinical pharmacists' judgment.

METHODS

This retrospective study included adult patients with a pharmacy dosing consult who received ≥1 dose of vancomycin and ≥1 serum vancomycin level documented between January 1, 2018, and December 31, 2019. Patients with baseline serum creatinine ≥2 mg/dL, weight ≥100 kg, receiving renal replacement therapy, AKI prior to vancomycin therapy, or vancomycin ordered only for surgical prophylaxis were excluded. The primary analysis was incidence of AKI adjusted for baseline serum creatinine, age, and intensive care unit admission. A secondary outcome was adjusted incidence of an abnormal trough value (<10 or >20 μg/mL).

RESULTS

The study included 3459 encounters. Incidence of AKI was 21% for Bayesian software (n = 659), 22% for the nomogram (n = 303), and 32% for trough-guided dosing (n = 2497). Compared with trough-guided dosing, incidence of AKI was lower in the Bayesian (adjusted odds ratio [OR] = 0.72, 95% confidence interval [CI]: 0.58-0.89) and the nomogram (adjusted OR = 0.71, 95% CI: 0.53-0.95) groups. Compared with trough-guided dosing, abnormal trough values were less common in the Bayesian group (adjusted OR = 0.83, 95% CI: 0.69-0.98).

CONCLUSION AND RELEVANCE

Study results suggest that use of AUC-guided Bayesian software reduces the incidence of AKI and abnormal trough values compared with trough-guided dosing.

Clinical application of vancomycin TDM in ventilated patients with gastrointestinal cancer: a propensity-matched analysis

BACKGROUND

Therapeutic drug monitoring (TDM) of vancomycin is widely recommended for clinical treatment. Due to the complexity of 24-h area under the curve (AUC) guided vancomycin monitoring in clinical practice, the vancomycin trough level remains the most common and practical method. The purpose of this study was designed to investigate the differences in the safety and efficacies of vancomycin TDM based on the two different monitoring methods, and further explore the clinical application of trough-guided vancomycin monitoring in patients with gastrointestinal cancer requiring mechanical ventilation.

METHODS

We included a total of 78 gastrointestinal cancer patients who required mechanical ventilation due to various diseases. All patients included in this study were aged 18 years or older and were treated with intravenous vancomycin therapy for more than 2 days due to documented or suspected Gram-positive bacterial infections, and have at least one available vancomycin plasma concentration. First, we compared the safety and efficacies of vancomycin TDM based on different monitoring methods as trough-guided monitoring or AUC-guided monitoring. Then, based on whether the initial vancomycin concentration achieving the target trough concentration (less than 48 h), patients were divided into early and delayed groups, and the clinical factors were compared between them. The primary endpoints include the incidence of new-onset acute kidney injury (AKI) or renal replacement therapy (RRT), clinical success rate and 28-day all-cause mortality. Finally, the overall relationship between trough concentration and potential covariates is screened by univariate and multivariate analysis to explore potential information covariates.

RESULTS

The research revealed that patients with gastrointestinal cancer exhibited significantly lower initial vancomycin trough concentrations (median [interquartile range (IQR)]: 6.90[5.28-11.20] mg/L). And there were no statistically significant differences in the safety and efficacies of vancomycin TDM based on the two different monitoring methods for the primary endpoint. Moreover, base on trough-guided vancomycin monitoring, the early group demonstrated a notably shorter duration of mechanical ventilation compared with the delayed group (χ2 = 4.532; p < 0.05; Fig. 2E). Propensity score weighting further confirmed that the duration of mechanical ventilation (χ2 = 6.607; p < 0.05; Fig. 2F) and duration of vasoactive agent (χ2 = 6.106; p < 0.05; Fig. 2D) were significantly shorter in the early group compared with delayed group. Multivariate regression analysis revealed that Cystatin C (Cys-C) was the most important variable for vancomycin target trough achievement (odds ratio, 5.274; 95% CI, 1.780 to 15.627; p = 0.003).

CONCLUSIONS

Trough-guided vancomycin monitoring is a simple and effective marker of TDM for ventilated patients with gastrointestinal cancer. Timely achievement of target trough concentrations for vancomycin can improve partial clinical outcomes in Gram-positive bacterial infections. Cys-C level is a potentially valuable parameter for predicting the vancomycin concentration.

Status and Quality of Guidelines for Therapeutic Drug Monitoring Based on AGREE II Instrument

BACKGROUND

With the progress of therapeutic drug monitoring (TDM) technology and the development of evidence-based medicine, many guidelines were developed and implemented in recent decades.

OBJECTIVE

The aim was to evaluate the current status of TDM guidelines and provide suggestions for their development and updates based on Appraisal of Guidelines for Research and Evaluation (AGREE) II.

METHODS

The TDM guidelines were systematically searched for among databases including PubMed, Embase, China National Knowledge Infrastructure, Wanfang Data, and the Chinese biomedical literature service system and the official websites of TDM-related associations. The search period was from inception to 6 April 2023. Four researchers independently screened the literature and extracted data. Any disagreement was discussed and reconciled by another researcher. The quality of guidelines was assessed using the AGREE II instrument.

RESULTS

A total of 92 guidelines were included, including 57 technical guidelines, three management guidelines, and 32 comprehensive guidelines. The number of TDM guidelines has gradually increased since 1979. The United States published the most guidelines (20 guidelines), followed by China (15 guidelines) and the United Kingdom (ten guidelines), and 23 guidelines were developed by international organizations. Most guidelines are aimed at adult patients only, while 28 guidelines include special populations. With respect to formulation methods, there are 23 evidence-based guidelines. As for quality evaluation results based on AGREE II, comprehensive guidelines scored higher (58.16%) than technical guidelines (51.36%) and administrative guidelines (50.00%).

CONCLUSION

The number of TDM guidelines, especially technical and comprehensive ones, has significantly increased in recent years. Most guidelines are confronted with the problems of unclear methodology and low quality of evidence according to AGREE II. More evidence-based research on TDM and high-quality guideline development is recommended to promote individualized therapy.

Fluorimetric monitoring of vancomycin using an allosteric probe-initiated sensing platform

Vancomycin is the first-line drug for infections of methicillin-resistant Staphylococcus aureus (MRSA) and multi-drug-resistant bacteria. The effective therapeutic concentration range of vancomycin is narrow, so it's essential to implement vancomycin therapeutic drug monitoring. However, conventional detection methods have disadvantages of expensive equipment, complicated operation, or poor reproducibility. Herein, a fluorescent sensing platform initiated by an allosteric probe was constructed for simple and sensitive monitoring of vancomycin at a low cost. The key point of this platform is the well-designed allosteric probe, which comprises an aptamer and a trigger sequence. When vancomycin exists, the combination of vancomycin and the aptamer will lead to a conformational change of the allosteric probe, thus exposing the trigger sequence. The trigger can react with the molecular beacon (MB) to generate fluorescent signals. In addition, the allosteric probe combined with hybridization chain reaction (HCR) was applied to develop an amplified platform, the linear range is from 0.5 μg mL^-1 to 50 μg mL^-1 with the limit of detection (LOD) of 0.26 μg mL^-1. Most importantly, this allosteric probe-initiated sensing platform shows good detection ability in human serum samples, and it also indicates great correlation and accuracy compared with HPLC. The present simple and sensitive allosteric probe-initiated platform has the potential to support the therapeutic drug monitoring of vancomycin, which is of great significance to promote the rational use of antibiotics in clinics.

External validation of population pharmacokinetic models of vancomycin in postoperative neurosurgical patients

OBJECTIVE

Vancomycin is commonly used in the prevention and treatment of intracranial infections in postoperative neurosurgical patients with narrow therapeutic window and large pharmacokinetic variations. Several population pharmacokinetic (PPK) models of vancomycin have been established for neurosurgical patients. But comprehensive external evaluation has not been performed for almost all models. The objective of this study was to evaluate the predictive ability of published vancomycin PPK models in adult postoperative neurosurgical patients using an independent dataset.

METHOD

PubMed, Embase and China National Knowledge Internet databases were searched to identify published vancomycin PPK models in adult postoperative neurosurgical patients. Prediction-based and simulation-based diagnostics were used to evaluate model predictability. Bayesian forecasting was used to assess the influence of prior concentration on model prediction performance.

RESULT

A total of 763 vancomycin plasma concentrations from 493 postoperative neurosurgical patients were included in the external dataset. Eight population pharmacokinetic models of vancomycin in postoperative neurosurgical patients were included and evaluated. The model by Zhang et al. exhibited the best predictive performance in prediction-based diagnostics and prediction-corrected visual predictive checks, followed by the model by Shen et al. The predictive performance of other models was not satisfactory. The normalized predictive distribution error test shows that none of the models is suitable to describe our data. The predictive performance of vancomycin models was obviously improved by maximum a posteriori Bayesian forecasting.

CONCLUSION

The published PPK models for adult postoperative neurosurgical patients show extensive variation in predictive performance in our patients. Although it is challenging to recommend initial doses of vancomycin from these predictive models, the combination of model-based prediction and therapeutic drug monitoring can be used for dose optimization.

Awareness, perception, and barriers of healthcare providers toward the revised consensus guideline for therapeutic monitoring of vancomycin

Background

A revised consensus guideline published in 2020 recommended transitioning vancomycin monitoring to the area under the concentration-time curve over 24 h to minimum inhibitory concentration (AUC₂₄/MIC). The decision to transition to AUC₂₄/MIC monitoring or to continue trough-based monitoring is made at the institutional level and is influenced by several factors, including healthcare providers and system-related factors. Changing current practices is expected to be difficult, and it is important to understand healthcare providers' perceptions and potential barriers before the transition. This study assessed the awareness and perception of physicians and pharmacists toward the revised guideline and identified barriers to their implementation in Kuwait.

Methods

A cross-sectional survey that employed a self-administered questionnaire was used. A random sample of physicians (n = 390), clinical microbiologists (n = 37), and clinical pharmacists (n = 48) across six Kuwaiti public hospitals were surveyed. Descriptive and comparative statistical analyses were performed. Factors associated with awareness and perceptions among the participants were identified.

Results

The response rate was 85.3% (n = 431). Participants had a high (median = 75%) awareness score for the updated vancomycin guideline, as well as a positive perception (median = 5). The main factor identified to affect the awareness and perception of participants following the group analysis was the years of experience. The main barriers identified were a lack of training to perform vancomycin AUC₂₄ calculations, a lack of accurate documentation sample time, and a long turnaround time for serum levels, which might hinder the implementation of the updated guideline.

Conclusion

Physicians, clinical microbiologists, and pharmacists working in Kuwait public hospitals were aware of the 2020 vancomycin monitoring guidelines with positive perceptions. Participants agreed on the several barriers to transitioning to the AUC₂₄/MIC approach, which should be considered by stakeholders before implementation.

What Is the Best Vancomycin Therapeutic Drug Monitoring Parameter to Assess Efficacy? A Critical Review of Experimental Data and Assessment of the Need for Individual Patient Minimum Inhibitory Concentration Value

Therapeutic drug monitoring is recommended for the use of vancomycin, but a recent widely publicized US medical society consensus statement has changed the suggested optimal method(s) of dose adjustment. Specifically, 24 h area under the curve (AUC₂₄)-based monitoring is has been recommended for vancomycin in preference to monitoring of trough concentrations. One reason cited for this change is the claim that AUC₂₄ is a superior correlate to efficacy than trough (Cmin). Evidence from a number of retrospective analyses have been critically reviewed and determined to have weaknesses. This narrative review focuses on the experimental studies performed in vivo in animal models of infection and in vitro to determine the extent to which these data may provide a compelling distinction between pharmacokinetic/pharmacodynamics (PKPD) parameters that may translate to clinical use in therapeutic drug monitoring. Animal in vivo studies have been presented at conferences, but no original peer reviewed studies could be found that compare various PKPD parameters. These conference proceeding findings were supportive but unconvincing, even though they were favorably presented subsequently in review articles and clinical practice guidelines. In vitro data are somewhat conflicting, but the range of concentrations may play a role in the discrepancies found. It has been suggested that MIC may be assumed to have a value of 1 mg/L; however, it can be demonstrated that this assumption may lead to considerable discrepancy from results with an actual MIC value. The AUC₂₄ parameter has been weighed against the percentage of time above the MIC (%T > MIC) as a comparative PKPD parameter, yet this may be an inappropriate comparison for vancomycin since all clinically useful dosing provides 100% T > MIC. Regardless, there is a distinction between clinical TDM parameters and PKPD parameters, so, in practice, the change to AUC₂₄:MIC based on animal experiments and in vitro evidence for vancomycin may be premature.

Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill

Purpose

To assess the agreement in 24-hour area under the curve (AUC₂₄) value estimates between commonly used vancomycin population pharmacokinetic models in the critically ill.

Materials and Methods

Adults admitted to intensive care who received intravenous vancomycin and had a serum vancomycin concentration available were included. AUC₂₄ values were determined using Tucuxi (revision cd7bd7a8) for dosing intervals with a vancomycin concentration using three models (Goti 2018, Colin 2019, and Thomson 2009) previously evaluated in the critically ill. AUC₂₄ values were categorized as subtherapeutic (<400 mg·h/L), therapeutic (400-600 mg·h/L), or toxic (>600 mg·h/L), assuming a minimum inhibitory concentration of 1 mg/L. AUC₂₄ value categorization was compared across the three models and reported as percent agreement.

Results

Overall, 466 AUC₂₄ values were estimated in 188 patients. Overall, 52%, 42%, and 47% of the AUC₂₄ values were therapeutic for the Goti, Colin, and Thomson models, respectively. The agreement of AUC₂₄ values between all three models was 48% (223/466), Goti-Colin 59% (193/466), Goti-Thomson 68% (318/466), and Colin-Thomson 67% (314/466).

Conclusion

In critically ill patients, vancomycin AUC₂₄ values obtained from different pharmacokinetic models are often discordant, potentially contributing to differences in dosing decisions. This highlights the importance of selecting the optimal model.

Population pharmacokinetic model of vancomycin in postoperative neurosurgical patients

Objective: Vancomycin is commonly used in postoperative neurosurgical patients for empirical anti-infective treatment due to the low success rate of bacterial culture in cerebrospinal fluid (about 20%) and the high mortality of intracranial infection. At conventional doses, the rate of target achievement for vancomycin trough concentration is low and the pharmacokinetics of vancomycin varies greatly in these patients, which often leads to treatment failure. The objective of this study was to establish a population pharmacokinetic (PPK) model of vancomycin in postoperative neurosurgical patients for precision medicine.

Method: A total of 895 vancomycin plasma concentrations from 560 patients (497 postoperative neurosurgical patients) were retrospectively collected. The model was analyzed by nonlinear mixed effects modeling method. One-compartment model and mixed residual model was employed. The influence of covariates on model parameters was tested by forward addition and backward elimination. Goodness-of-fit, bootstrap and visual predictive check were used for model evaluation. Monte Carlo simulations were employed for dosing strategies with AUC₂₄ targets 400–600.

Result: Estimated glomerular filtration rate (eGFR), body weight (BW) and mannitol had significant influence on vancomycin clearance (CL). eGFR(mL/min)=144×(Scr/a)b×0.993age, for female, a = 0.7, Scr ≤ 0.7 mg/dl, b = −0.329, Scr > 0.7 mg/dl, b = −1.209; for male, a = 0.9, Scr ≤ 0.9 mg/dl, b = −0.411, Scr > 0.9 mg/dl, b = −1.210. Vancomycin clearance was accelerated when co-medicated with mannitol and increased with eGFR and BW. In the final model, the population typical value is 7.98 L/h for CL and 60.2 L for apparent distribution volume, CL (L/h)=7.98×(eGFR/115.2)0.8×(BW/70)0.3×eA, where A = 0.13 when co-medicated with mannitol, otherwise A = 0. The model is stable and effective, with good predictability.

Conclusion: In postoperative neurosurgical patients, a higher dose of vancomycin may be required due to the augmented renal function and the commonly used mannitol, especially in those with high body weight. Our vancomycin PPK model could be used for individualized treatment in postoperative neurosurgical patients.

Review and evaluation of vancomycin dosing guidelines for obese individuals

INTRODUCTION

Vancomycin dosing decisions are informed by factors such as body weight and renal function. It is important to understand the impact of obesity on vancomycin pharmacokinetics and how this may influence dosing decisions. Vancomycin dosing guidelines use varied descriptors of body weight and renal function. There is uncertainty whether current dosing guidelines result in attainment of therapeutic targets in obese individuals.

AREAS COVERED

Literature was explored using PubMed, Embase and Google Scholar for articles from January 1980 to July 2021 regarding obesity-driven physiological changes, their influence on vancomycin pharmacokinetics and body size descriptors and renal function calculations in vancomycin dosing. Pharmacokinetic simulations reflective of international vancomycin dosing guidelines were conducted to evaluate the ability of using total, ideal and adjusted body weight, as well as Cockcroft-Gault and CKD-EPI equations to attain an area-under-the-curve to minimum inhibitory concentration ratio (AUC₂₄/MIC) target (400-650) in obese individuals.

EXPERT OPINION

Vancomycin pharmacokinetics in obese individuals remains debated. Guidelines that determine loading doses using total body weight, and maintenance doses adjusted based on renal function and adjusted body weight, may be most appropriate for obese individuals. Use of ideal body weight leads to subtherapeutic vancomycin exposure and underestimation of renal function.