Population pharmacokinetics and dose simulation of vancomycin in critically ill patients during high-volume haemofiltration

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.

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.

Dose Tailoring of Vancomycin Through Population Pharmacokinetic Modeling Among Surgical Patients in Pakistan

Background: Vancomycin is a narrow therapeutic agent, and it is necessary to optimize the dose to achieve safe therapeutic outcomes. The purpose of this study was to identify the significant covariates for vancomycin clearance and to optimize the dose among surgical patients in Pakistan. Methods: Plasma concentration data of 176 samples collected from 58 surgical patients treated with vancomycin were used in this study. A population pharmacokinetic model was developed on NONMEM^® using plasma concentration-time data. The effect of all available covariates was evaluated on the pharmacokinetic parameters of vancomycin by stepwise covariate modeling. The final model was evaluated using bootstrap, goodness-of-fit plots, and visual predictive checks. Results: The pharmacokinetics of vancomycin followed a one-compartment model with first-order elimination. The vancomycin clearance (CL) and volume of distribution (Vd) were 2.45 L/h and 22.6 l, respectively. Vancomycin CL was influenced by creatinine clearance (CRCL) and body weight of the patients; however, no covariate was significant for its effect on the volume of distribution. Dose tailoring was performed by simulating dosage regimens at a steady state based on the CRCL of the patients. The tailored doses were 400, 600, 800, and 1,000 mg for patients with a CRCL of 20, 60, 100, and 140 ml/min, respectively. Conclusion: Vancomycin CL is influenced by CRCL and body weight of the patient. This model can be helpful for the dose tailoring of vancomycin based on renal status in Pakistani patients.

Dose Optimization of Vancomycin for Critically Ill Patients Undergoing CVVH: A Prospective Population PK/PD Analysis

The optimal dose of vancomycin in critically ill patients receiving continuous venovenous hemofiltration (CVVH) remains unclear. The objective of this study was to identify factors that significantly affect pharmacokinetic profiles and to further investigate the optimal dosage regimens for critically ill patients undergoing CVVH based on population pharmacokinetics and pharmacodynamic analysis. A prospective population pharmacokinetic analysis was performed at the surgical intensive care unit in a level A tertiary hospital. We included 11 critically ill patients undergoing CVVH and receiving intravenous vancomycin. Serial blood samples were collected from each patient, with a total of 131 vancomycin concentrations analyzed. Nonlinear mixed effects models were developed using NONMEM software. Monte Carlo Simulation was used to optimize vancomycin dosage regimens. A two-compartment model with first-order elimination was sufficient to characterize vancomycin pharmacokinetics for CVVH patients. The population typical vancomycin clearance (CL) was 1.15 L/h and the central volume of distribution was 16.9 L. CL was significantly correlated with ultrafiltration rate (UFR) and albumin level. For patients with normal albumin and UFR between 20 and 35 mL/kg/h, the recommended dosage regimen was 10 mg/kg qd. When UFR was between 35 and 40 mL/kg/h, the recommended dosage regimen was 5 mg/kg q8h. For patients with hypoalbuminemia and UFR between 20 and 25 mL/kg/h, the recommended dosage regimen was 5 mg/kg q8h. When UFR was between 25 and 40 mL/kg/h, the recommended dosage regimen was 10 mg/kg q12h. We recommend clinicians choosing the optimal initial vancomycin dosage regimens for critically ill patients undergoing CVVH based on these two covariates.

Pharmacokinetics and Target Attainment of Antibiotics in Critically Ill Children: A Systematic Review of Current Literature

BACKGROUND

Pharmacokinetics (PK) are severely altered in critically ill patients due to changes in volume of distribution (Vd) and/or drug clearance (Cl). This affects the target attainment of antibiotics in critically ill children. We aimed to identify gaps in current knowledge and to compare published PK parameters and target attainment of antibiotics in critically ill children to healthy children and critically ill adults.

METHODS

Systematic literature search in PubMed, EMBASE and Web of Science. Articles were labelled as relevant when they included information on PK of antibiotics in critically ill, non-neonatal, pediatric patients. Extracted PK-parameters included Vd, Cl, (trough) concentrations, AUC, probability of target attainment, and elimination half-life.

RESULTS

50 relevant articles were identified. Studies focusing on vancomycin were most prevalent (17/50). Other studies included data on penicillins, cephalosporins, carbapenems and aminoglycosides, but data on ceftriaxone, ceftazidime, penicillin and metronidazole could not be found. Critically ill children generally show a higher Cl and larger Vd than healthy children and critically ill adults. Reduced target-attainment was described in critically ill children for multiple antibiotics, including amoxicillin, piperacillin, cefotaxime, vancomycin, gentamicin, teicoplanin, amikacin and daptomycin. 38/50 articles included information on both Vd and Cl, but a dosing advice was given in only 22 articles.

CONCLUSION

The majority of studies focus on agents where TDM is applied, while other antibiotics lack data altogether. The larger Vd and higher Cl in critically ill children might warrant a higher dose or extended infusions of antibiotics in this patient population to increase target-attainment. Studies frequently fail to provide a dosing advice for this patient population, even if the necessary information is available. Our study shows gaps in current knowledge and encourages future researchers to provide dosing advice for special populations whenever possible.

Pharmacokinetics of and maintenance dose recommendations for vancomycin in severe pneumonia patients undergoing continuous venovenous hemofiltration with the combination of predilution and postdilution

PURPOSE

Therapeutic vancomycin levels are difficult to maintain in severe pneumonia patients who are receiving IV vancomycin therapy while on continuous venovenous hemofiltration (CVVH). The objective of this study was to determine the pharmacokinetics and maintenance dose recommendations of vancomycin in severe pneumonia patients receiving CVVH.

METHODS

A prospective study was conducted in the intensive care unit of a university hospital. Ten severe pneumonia patients receiving vancomycin and CVVH treatment were determined the initial and steady-state pharmacokinetics of vancomycin. CVVH was performed in mixed predilution and postdilution mode with a blood flow rate of 180 mL/min and an ultrafiltrate flow rate of 30-40 mL/kg/h. Group A received an initial dose of 500 mg only, whereas group B received 500 mg every 12 h until steady state is achieved. Serum and ultrafiltrate were collected over 12 h after infusion of vancomycin.

RESULTS

After initial dosing, the mean sieving coefficient (SC) was 0.72 ± 0.02, and CVVH clearance (CL_CVVH, 1.35 ± 0.03 L/h) constituted 60.55% ± 13.69% of total vancomycin clearance (CL_tot, 2.36 ± 0.72 L/h). When steady state was reached, the SC of the patients was 0.71 ± 0.03, and the CL_CVVH (1.34 ± 0.06 L/h) accounted for 66.96% ± 6.05% of the CL_tot (2.03 ± 0.27 L/h). The recommended maintenance dose for vancomycin in severe pneumonia patients was 400-650 mg every 12 h, which was calculated based on CL_tot, to achieve a trough concentration of 15-20 mg/L at steady state.

CONCLUSIONS

Single administration or multiple administration does not affect SC and CL_CVVH. Owing to therapeutic vancomycin levels is difficult to maintain in severe pneumonia patients who are receiving IV vancomycin therapy while on CVVH, close monitoring of serum trough concentrations is required.

External Evaluation of Population Pharmacokinetic Models of Vancomycin in Large Cohorts of Intensive Care Unit Patients

Dosing of vancomycin is often guided by therapeutic drug monitoring and population pharmacokinetic models in the intensive care unit (ICU). The validity of these models is crucial, as ICU patients have marked pharmacokinetic variability. Therefore, we set out to evaluate the predictive performance of published population pharmacokinetic models of vancomycin in ICU patients. The PubMed database was used to search for population pharmacokinetic models of vancomycin in adult ICU patients. The identified models were evaluated in two independent data sets which were collected from two large hospitals in the Netherlands (Amsterdam UMC, Location VUmc, and OLVG Oost). We also tested a one-compartment model with fixed values for clearance and volume of distribution, in which a clinical standard dosage regimen (SDR) was mimicked to assess its predictive performance. Prediction error was calculated to assess the predictive performance of the models. Six models plus the SDR model were evaluated. The model of Roberts et al. (J. A. Roberts, F. S. Taccone, A. A. Udy, J.-L. Vincent, F. Jacobs, and J. Lipman, Antimicrob Agents Chemother 55:2704-2709, 2011, https://doi.org/10.1128/AAC.01708-10) performed satisfactorily, with mean and median values of prediction error of 5.1% and -7.5%, respectively, for Amsterdam UMC, Location VUmc, patients, and -12.6% and -17.2% respectively, for OLVG Oost patients. The other models, including the SDR model, yielded high mean values (-49.7% to 87.7%) and median values (-56.1% to 66.1%) for both populations. In conclusion, only the model of Roberts et al. was able to validly predict the concentrations of vancomycin for our data, whereas other models and standard dosing were largely inadequate. Extensive evaluation should precede the adoption of any model in clinical practice for ICU patients.

Predicting the dose of vancomycin in ICU patients receiving different types of RRT therapy: a model-based meta-analytic approach

AIM

Previous pharmacokinetic (PK) studies have proposed various dosing regimens for vancomycin in intensive care unit (ICU) patients undergoing renal replacement therapy (RRT), but all are restricted to specific RRT modalities. To be useful in practice, a population PK model would need to predict vancomycin clearance during any RRT modality. Development of such a model is feasible using meta-analysis of published summarized estimates of vancomycin PK parameters. Our aims were: (i) to develop and validate a population PK model for vancomycin that takes into account any RRT modalities, and (ii) to predict vancomycin dosing for RRT patients in ICU.

METHODS

Vancomycin pharmacokinetics were assumed to be two-compartmental, total body clearance being the sum of non-RRT clearance and RRT-induced clearance. Drug disposition and non-RRT clearance parameters were estimated by systematic review and meta-analysis of previously published parameter estimates. The relationship between RRT-induced clearance and RRT flowrate settings was assessed using a model-based meta-analysis. Prediction performances of the PK model were assessed using external data.

RESULTS

The meta-analyses of disposition parameters, non-RRT clearance and RRT-induced clearance included 11, 6 and 38 studies (84 RRT clearance measurements) respectively. The model performed well in predicting external individual PK data. Individual vancomycin concentrations during RRT were accurately predicted using Bayesian estimation based solely on pre-RRT measurements.

CONCLUSIONS

The PK model allowed accurate prediction of the vancomycin pharmacokinetics during RRT in ICU patients. Based on the model of RRT-induced clearance, an appropriate adjustment of the vancomycin dosing regimen could be proposed for any kind of flowrate settings.

Population pharmacokinetic analysis of vancomycin in pediatric continuous renal replacement therapy

BACKGROUND AND OBJECTIVES

Dosing of vancomycin in pediatric patients undergoing continuous venous-venous hemodiafiltration (CVVHDF) is challenging. Characterization of vancomycin pharmacokinetics can assist with dosing and attainment of goal serum concentrations.

DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS

Patients less than 19 years of age who received vancomycin and had post-dose vancomycin concentrations while undergoing CVVHDF were identified. Data collection included the following: patient demographics, vancomycin dosing and serum concentrations, CVVHDF variables, serum creatinine (SCR), blood urea nitrogen (BUN), albumin, hematocrit, and urine output. Fat-free mass was calculated. Data were summarized with descriptive statistical methods, and population pharmacokinetic analysis was performed with NONMEM 7.2 and PDx-Pop 5.2. Simulation was performed to identify dosing regimens with the highest percentage of goal serum concentration < 20 mg/L and AUC_0-24:MIC ≥ 400 attainment.

RESULTS

A total of 138 patients met study criteria (45.6% male, median age 4.9 years (IQR (1.0, 14.5))). Mean vancomycin dose was 14.3 ± 1.6 mg/kg/dose (19.5 ± 3.0 mg/kg/dose by FFM). Patients had a median of six (IQR 2, 12) vancomycin serum concentrations sampled 13.6 ± 8.4 h after the dose, and the mean vancomycin serum concentration was 11.3 ± 3.4 mg/L. Vancomycin pharmacokinetics were characterized by a two-compartment model with allometric scaling on fat-free mass and significant covariates of SCR, BUN, dialysate flow rate, and ultrafiltration rate on clearance. Simulation identified doses of 40-50 mg/kg/day that divided every 8-12 h had the highest percentage of patients with a serum concentration < 20 mg/L and an AUC_0-24:MIC ≥ 400.

CONCLUSIONS

Vancomycin pharmacokinetics are characterized by fat-free mass, serum creatinine, blood urea nitrogen, dialysate flow rate, and ultrafiltration rate in the pediatric CVVHDF population. Dosing of 40-50 mg/kg/day on fat-free mass divided every 8-12 h with frequent vancomycin serum sampling is recommended.

Population pharmacokinetics of vancomycin in critically ill patients receiving prolonged intermittent renal replacement therapy

OBJECTIVES

The aim of this study was to describe the population pharmacokinetics of vancomycin during prolonged intermittent renal replacement therapy (PIRRT) in critically ill patients with acute kidney injury.

METHODS

Critically ill patients prescribed vancomycin across two sites had blood samples collected during one to three dosing intervals during which PIRRT was performed. Plasma samples were assayed with a validated immunoassay method. Population pharmacokinetic analysis and Monte Carlo simulations were performed using Pmetrics^®. The target vancomycin exposures were the area under the concentration-time curve within a 24-h period (AUC_0-24)/minimum inhibitory concentration (MIC) ratio of 400 for efficacy and AUC_0-24 700 for toxicity.

RESULTS

Eleven critically ill patients (seven male) were enrolled and contributed 192 plasma samples. The patient's mean ± standard deviation (SD) age, weight and body mass index (BMI) were 57 ± 13 years, 98 ± 43 kg and 31 ± 9 kg/m², respectively. A two-compartment linear model adequately described the data. The mean ± SD population pharmacokinetic parameter estimates were PIRRT clearance (CL) 3.47 ± 1.99 L/h, non-PIRRT CL 2.15 ± 2.07 L/h, volume of distribution of the central compartment (Vc) 41.85 ± 24.33 L, distribution rate constant from central to peripheral compartment 5.97 ± 7.93 per h and from peripheral to central compartment 5.29 ± 6.65 per h. Assuming a MIC of 1 mg/L, vancomycin doses of 25 mg/kg per day are suggested to be efficacious, whilst minimising toxic, exposures.

CONCLUSIONS

This is the first population pharmacokinetic study of vancomycin in patients receiving PIRRT and we observed large pharmacokinetic variability. Empirically, weight-based doses that are appropriate for the duration of PIRRT, should be selected and supplemented with therapeutic drug monitoring.

Optimizing the Clinical Use of Vancomycin

The increasing number of infections produced by beta-lactam-resistant Gram-positive bacteria and the morbidity secondary to these infections make it necessary to optimize the use of vancomycin. In 2009, the American Society of Health-System Pharmacists, the Infectious Diseases Society of America, and the Society of Infectious Disease Pharmacists published specific guidelines about vancomycin dosage and monitoring. However, these guidelines have not been updated in the past 6 years. This review analyzes the new available information about vancomycin published in recent years regarding pharmacokinetics and pharmacodynamics, serum concentration monitoring, and optimal vancomycin dosing in special situations (obese people, burn patients, renal replacement therapy, among others). Vancomycin efficacy is linked to a correct dosage which should aim to reach an area under the curve (AUC)/MIC ratio of ≥400; serum trough levels of 15 to 20 mg/liter are considered a surrogate marker of an AUC/MIC ratio of ≥400 for a MIC of ≤1 mg/liter. For Staphylococcus aureus strains presenting with a MIC >1 mg/liter, an alternative agent should be considered. Vancomycin doses must be adjusted according to body weight and the plasma trough levels of the drug. Nephrotoxicity has been associated with target vancomycin trough levels above 15 mg/liter. Continuous infusion is an option, especially for patients at high risk of renal impairment or unstable vancomycin clearance. In such cases, vancomycin plasma steady-state level and creatinine monitoring are strongly indicated.

Method Based on the β-Lactamase PenPC Fluorescent Labeled for β-Lactam Antibiotic Quantification in Human Plasma

Recently, Wong et al. have successfully developed a fluorescent biosensor based on the PenPC β-lactamase which changes its intrinsic fluorescence in presence of β-lactam antibiotics (BLAs). Here, we studied systematically this correlation among the fluorescence change of the biosensor and the concentration of different BLAs aimed at developing a novel method for estimating the concentration of a wide range of BLAs. This method showed high precision and specificity and very low interference from clinically relevant samples. We were able to monitor the pharmacokinetics of meropenem in healthy volunteers as well as in an ill animal model too, indicating that the implemented method could be suitable for clinical practice.

Modeling for critically ill patients: An introduction for beginners

Models are mathematical tools used to describe real-world features. Therapeutic interventions in the field of critical care medicine may easily be translated into such models. Indeed, numerous variables influencing drug pharmacokinetics and pharmacodynamics are systematically documented in the intensive care unit over time. Organ failure, fluid shifts, other drug administration, and renal replacement therapy may cause changes in physiological values, such as body weight and composition, temperature, serum protein levels, arterial pH, and renal or hepatic function. Trials assessing the efficacy and safety of novel drugs usually exclude critically ill patients, and guidelines regarding drug dosage rarely apply to such patients. Modeling in the critically ill may allow physicians to inform decisions related to therapeutic interventions, particularly relating to infectious diseases. However, few clinicians are familiar with these methods. Here, we present a current overview of population pharmacokinetic and pharmacodynamic models applicable in critically ill patients aimed at nonspecialists and then emphazize recent potential of modeling for optimizing treatments and care in the intensive care unit.

[Septic shock in intensive care units. Current focus on treatment]

Essential therapeutic principles in children with septic shock persist over time, although some new concepts have been recently incorporated, and fully awareness of pediatricians and intensivists is essential. Fluid resuscitation is a fundamental intervention, but the kind of ideal fluid has not been established yet, as each of these interventions has specific limitations and there is no evidence supportive of the superiority of one type of fluid. Should septic shock persists despite adequate fluid resuscitation, the use of inotropic medication and/or vasopressors is indicated. New vasoactive drugs can be used in refractory septic shock caused by vasopressors, and the use of hydrocortisone should be considered in children with suspected adrenal insufficiency, as it reduces the need for vasopressors. The indications for red blood cells transfusion or the optimal level of glycemia are still controversial, with no consensus on the threshold value for the use of these blood products or the initiation of insulin administration, respectively. Likewise, the use of high-volume hemofiltration is a controversial issue and further study is needed on the routine recommendation in the course of septic shock. Nutritional support is crucial, as malnutrition is a serious complication that should be properly prevented and treated. The aim of this paper is to provide update on the most recent advances as concerns the treatment of septic shock in the pediatric population.

How can we ensure effective antibiotic dosing in critically ill patients receiving different types of renal replacement therapy?

Determining appropriate antibiotic dosing for critically ill patients receiving renal replacement therapy (RRT) is complex. Worldwide unstandardized and heterogeneous prescribing of RRT as well as altered patient physiology and pathogen susceptibility all cause drug disposition to be much different to that seen in non-critically ill patients. Significant changes to pharmacokinetic parameters, including volume of distribution and clearance, could be expected, in particular, for antibiotics that are hydrophilic with low plasma protein binding and that are usually primarily eliminated by the renal system. Antibiotic clearance is likely to be significantly increased when higher RRT intensities are used. The combined effect of these factors that alter antibiotic disposition is that non-standard dosing strategies should be considered to achieve therapeutic exposure. In particular, an aggressive early approach to dosing should be considered and this may include administration of a 'loading dose', to rapidly achieve therapeutic concentrations and maximally reduce the inoculum of the pathogen. This approach is particularly important given the pharmacokinetic changes in the critically ill as well as the increased likelihood of less susceptible pathogens. Dose individualization that applies knowledge of the RRT and patient factors causing altered pharmacokinetics remains the key approach for ensuring effective antibiotic therapy for these patients. Where possible, therapeutic drug monitoring should also be used to ensure more accurate therapy. A lack of pharmacokinetic data for antibiotics during the prolonged intermittent RRT and intermittent hemodialysis currently limits evidence-based antibiotic dose recommendations for these patients.