Vancomycin Pharmacokinetics in Obese Patients with Sepsis or Septic Shock

The pharmacokinetics of antibiotics in patients with obesity: a systematic review and consensus guidelines for dose adjustments

Obesity can cause physiological changes resulting in antibiotic pharmacokinetic alterations and suboptimal drug exposures. This systematic review aimed to summarise the available evidence on this topic and provide guidance for dose adjustment of antibiotics in adult (age ≥18 years) patients with obesity (BMI >30 kg/m2). We searched PubMed, Embase, and CENTRAL databases to find relevant studies published between database inception and Dec 30, 2023. We initially identified 6113 studies, which became 4654 studies after duplicate removal, and 128 studies were included in the final review. β-lactam antibiotics were most commonly studied (57 studies), followed by the group of glycopeptides, lipoglycopeptides, and oxazolidinones (45 studies). The certainty of evidence was low or very low for all antibiotics and a meta-analysis was not possible due to the heterogeneity of study populations and methods. Obesity modestly alters the pharmacokinetics of β-lactam antibiotics, but evidence does not support routine dose adjustments. For aminoglycosides and glycopeptides, the impact of obesity on pharmacokinetics is evident and weight-based dosing is recommended. Data are sparse for other antibiotic classes and research needs are described. In the absence of robust pharmacokinetic data, therapeutic drug monitoring can be used to guide individualised dosing.

A Successful Experience of Individualized Vancomycin Dosing in Critically Ill Patients by Using a Loading Dose and Maintenance Dose

Background/Objective: Vancomycin, a hydrophilic glycopeptide antibiotic with bactericidal activity against Gram-positive microorganisms, is one of the most commonly used antibiotics un the intensive care unit (ICU). Different efforts have been made to achieve a therapeutically effective plasma concentration of vancomycin by using loading and subsequent maintenance doses on an individual basis, but this remains subject to debate. Our objective was to individualize a dosage regimen in a Chilean ICU to optimize the pharmacological treatment of vancomycin by using a population pharmacokinetic model. Methods: A quantitative descriptive study was carried out in 51 patients at the adult ICU, San Borja Arriarán Clinical Hospital in Santiago, Chile. The dose of vancomycin was calculated by using a population pharmacokinetic software, the Antibiotic Kinetics®, and was subsequently validated with plasma trough levels of the drug through a patient sample. Results: The most commonly prescribed loading dose was 1500 mg and the most commonly used maintenance dose was 1000 mg, three times a day. The measured blood plasma concentrations of each patient (16.98 ± 5.423 μg/mL) were compared with the concentrations calculated through the population pharmacokinetic model (14.33 ± 4.630 μg/mL, p < 0.05). In addition, a correlation was found between the software-calculated trough concentration versus the measured trough concentration for vancomycin, with a positive correlation between both variables established (R2 = 0.65; p < 0.0001). No renal side effects were observed in the treated patient group. Conclusions: In the present study, a vancomycin dosing model for critically ill patients, based on a population pharmacokinetic model, was successfully implemented for routine clinical practice.

Surgical Antibiotic Prophylaxis Dosing in Adult Patients with Obesity: A Comprehensive Review of Pharmacokinetic and Pharmacodynamic Data

Surgical antibiotic prophylaxis is an important measure to prevent postoperative surgical site infections. Current guideline recommendations do not treat obesity specifically, although it can affect pharmacokinetics and pharmacodynamics. The objective of this review was to synthesize current evidence on the need for obesity-related dosing adjustments in surgical antibiotic prophylaxis. MEDLINE and Cochrane Library were searched for studies investigating antibiotic prophylaxis dosing in surgical patients with obesity. Outcomes of interest were pharmacokinetic parameters such as plasma and interstitial fluid concentrations, area under the concentration time curve in plasma and in interstitial fluid, and other pharmacokinetic measures. Thirty studies investigating cefazolin, cefoxitin, cefuroxime, piperacillin/tazobactam, meropenem, ertapenem, metronidazole, vancomycin, ciprofloxacin, and gentamicin were included in this analysis. Except for metronidazole, cefoxitin, and gentamicin, there is currently no evidence suggesting the need for dosing adjustments.

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.

Selecting the Best Pharmacokinetic Models for a Priori Model-Informed Precision Dosing with Model Ensembling

BACKGROUND AND OBJECTIVE

When utilizing population pharmacokinetic (popPK) models for a priori dosage individualization, selecting the best model is crucial to obtain adequate doses. We developed and evaluated several model-selection and ensembling methods, using external evaluation on the basis of therapeutic drug monitoring (TDM) samples to identify the best (set of) models per patient for a priori dosage individualization.

METHODS

PK data and models describing both hospitalized patients (n = 134) receiving continuous vancomycin (26 models) and patients (n = 92) receiving imatinib in an outpatient setting (12 models) are included. Target attainment of four model-selection methods was compared with standard dosing: the best model based on external validation, uninformed model ensembling, model ensembling using a weighting scheme on the basis of covariate-stratified external evaluation, and model selection using covariates in decision trees that were subsequently ensembled.

RESULTS

Overall, the use of PK models improved the proportion of patients exposed to concentrations within the therapeutic window for both cohorts. Relative improvement of proportion on target for best model, unweighted, weighted, and decision trees were - 7.0%, 2.3%, 11.4%, and 37.0% (vancomycin method-development); 23.2%, 7.9%, 15.6%, and, 77.2% (vancomycin validation); 40.7%, 50.0%, 59.5%, and 59.5% (imatinib method-development); and 19.0%, 28.5%, 38.0%, and 23.8% (imatinib validation), respectively.

CONCLUSIONS

The best (set of) models per patient for a priori dosage individualization can be identified using a relatively small set of TDM samples as external evaluation. Adequately performing popPK models were identified while also excluding poor-performing models. Dose recommendations resulted in more patients within the therapeutic range for both vancomycin and imatinib. Prospective validation is necessary before clinical implementation.

Risk Factors Associated with Antibiotic Exposure Variability in Critically Ill Patients: A Systematic Review

(1) Background: Knowledge about the behavior of antibiotics in critically ill patients has been increasing in recent years. Some studies have concluded that a high percentage may be outside the therapeutic range. The most likely cause of this is the pharmacokinetic variability of critically ill patients, but it is not clear which factors have the greatest impact. The aim of this systematic review is to identify risk factors among critically ill patients that may exhibit significant pharmacokinetic alterations, compromising treatment efficacy and safety. (2) Methods: The search included the PubMed, Web of Science, and Embase databases. (3) Results: We identified 246 observational studies and ten clinical trials. The most studied risk factors in the literature were renal function, weight, age, sex, and renal replacement therapy. Risk factors with the greatest impact included renal function, weight, renal replacement therapy, age, protein or albumin levels, and APACHE or SAPS scores. (4) Conclusions: The review allows us to identify which critically ill patients are at a higher risk of not reaching therapeutic targets and helps us to recognize the extensive number of risk factors that have been studied, guiding their inclusion in future studies. It is essential to continue researching, especially in real clinical practice and with clinical outcomes.

External Validation of Obese/Critically Ill Vancomycin Population Pharmacokinetic Models in Critically Ill Patients Who Are Obese

Obesity combined with critical illness might increase the risk of acquiring infections and hence mortality. In this patient population the pharmacokinetics of antimicrobials vary significantly, making antimicrobial dosing challenging. The objective of this study was to assess the predictive performance of published population pharmacokinetic models of vancomycin in patients who are critically ill or obese for a cohort of critically ill patients who are obese. This was a multi-center retrospective study conducted at 2 hospitals. Adult patients with a body mass index of ≥30 kg/m2 were included. PubMed was searched for published population pharmacokinetic studies in patients who were critically ill or obese. External validation was performed using Monolix software. A total of 4 models were identified in patients who were obese and 5 models were identified in patients who were critically ill. In total, 138 patients who were critically ill and obese were included, and the most accurate models for these patients were the Goti and Roberts models. In our analysis, models in patients who were critically ill outperformed models in patients who were obese. When looking at the most accurate models, both the Goti and the Roberts models had patient characteristics similar to ours in terms of age and creatinine clearance. This indicates that when selecting the proper model to apply in practice, it is important to account for all relevant variables, besides obesity.

Population pharmacokinetics of antibacterial agents in the older population: a literature review

INTRODUCTION

Older individuals face an elevated risk of developing bacterial infections. The optimal use of antibacterial agents in this population is challenging because of age-related physiological alterations, changes in pharmacokinetics (PK) and pharmacodynamics (PD), and the presence of multiple underlying diseases. Therefore, population pharmacokinetics (PPK) studies are of great importance for optimizing individual treatments and prompt identification of potential risk factors.

AREA COVERED

Our search involved keywords such as 'elderly,' 'old people,' and 'geriatric,' combined with 'population pharmacokinetics' and 'antibacterial agents.' This comprehensive search yielded 11 categories encompassing 28 antibacterial drugs, including vancomycin, ceftriaxone, meropenem, and linezolid. Out of 127 studies identified, 26 (20.5%) were associated with vancomycin, 14 (11%) with meropenem, and 14 (11%) with piperacillin. Other antibacterial agents were administered less frequently.

EXPERT OPINION

PPK studies are invaluable for elucidating the characteristics and relevant factors affecting the PK of antibacterial agents in the older population. Further research is warranted to develop and validate PPK models for antibacterial agents in this vulnerable population.

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.

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.

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.

Comparison of Race and Non-Race Based Equations for Kidney Function Estimation in Critically Ill Thai Patients for Vancomycin Dosing

Empiric antibiotic dosing frequently relies on an estimate of kidney function based on age, serum creatinine (SCr), sex, and race (on occasion). New non-Race based estimated glomerular filtration rate (eGFR) equations have been published but their role to support dosing is not known. Here, we report on a population pharmacokinetic model of vancomycin that serves as a useful probe substrate of eGFR in critically ill Thai patients. Data were obtained from medical records during a 10-year period. A nonlinear mixed-effects modeling approach was conducted to estimate vancomycin parameters. Data from 208 critically ill patients (58.2% male and 36.0% septic shock) with 398 vancomycin concentrations were collected. Twenty-three covariates including 12 kidney function estimates were tested and ranked based on the model performance. The median [min, max] age, weight, and SCr was 69 [18, 97] years, 60.0 [27, 120] kg, and 1.53 [0.18, 7.15] mg/dL. The best base model was a one-compartment linear with zero-order input and proportional error model. A Thai specific eGFR equation not indexed to body surface area (BSA) model best predicted vancomycin clearance (CL). The typical value for volume of distribution and CL was 67.5 L and 1.22 L/h, respectively. A loading dose of 2000 mg followed by maintenance dose regimens based on eGFR is suggested. The Thai-GFR not indexed to BSA model best predicts vancomycin CL and dosing in the critically ill Thai population. A 5-10% absolute gain in the vancomycin probability of target attainment is expected with the use of this population specific GFR equation. This article is protected by copyright. All rights reserved.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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

Clinical Practice Guidelines for Therapeutic Drug Monitoring of Vancomycin in the Framework of Model-Informed Precision Dosing: A Consensus Review by the Japanese Society of Chemotherapy and the Japanese Society of Therapeutic Drug Monitoring

Background: To promote model-informed precision dosing (MIPD) for vancomycin (VCM), we developed statements for therapeutic drug monitoring (TDM). Methods: Ten clinical questions were selected. The committee conducted a systematic review and meta-analysis as well as clinical studies to establish recommendations for area under the concentration-time curve (AUC)-guided dosing. Results: AUC-guided dosing tended to more strongly decrease the risk of acute kidney injury (AKI) than trough-guided dosing, and a lower risk of treatment failure was demonstrated for higher AUC/minimum inhibitory concentration (MIC) ratios (cut-off of 400). Higher AUCs (cut-off of 600 μg·h/mL) significantly increased the risk of AKI. Although Bayesian estimation with two-point measurement was recommended, the trough concentration alone may be used in patients with mild infections in whom VCM was administered with q12h. To increase the concentration on days 1–2, the routine use of a loading dose is required. TDM on day 2 before steady state is reached should be considered to optimize the dose in patients with serious infections and a high risk of AKI. Conclusions: These VCM TDM guidelines provide recommendations based on MIPD to increase treatment response while preventing adverse effects.