Non steady state and steady state PKS Bayesian forecasting and vancomycin pharmacokinetics in ICU adult patients

New advances in management and treatment of cardiac implantable electronic devices infections

Cardiac implantable electronic devices (CIED) are increasingly used worldwide, and infection of these devices remains one of the most feared complications.CIED infections (CDIs) represent a challenge for physicians and the healthcare system in general as they require prolonged hospitalization and antibiotic treatment and are burdened by high mortality and high costs, so management of CDIs must be multidisciplinary.The exact incidence of CDIs is difficult to define, considering that it is influenced by various factors mainly represented by the implanted device and the type of procedure. Risk factors for CDIs could be divided into three categories: device related, patient related, and procedural related and the etiology is mainly sustained by Gram-positive bacteria; however, other etiologies cannot be underestimated. As a matter of fact, the two cornerstones in the treatment of these infections are device removal and antimicrobial treatment. Finally, therapeutic drug monitoring and PK/PD correlations should be encouraged in all patients with CDIs receiving antibiotic therapy and may result in a better clinical outcome and a reduction in antibiotic resistance and economic costs.In this narrative review, we look at what is new in the management of these difficult-to-treat infections.

A Meta-Analysis on the Performance of Cystatin C- versus Creatinine-based eGFR Equations in Predicting Vancomycin Clearance

BACKGROUND

The objective of this study was to compare the performance of cystatin C- and creatinine-based estimated glomerular filtration rate (eGFR) equations in predicting the clearance of vancomycin.

METHODS

MEDLINE and Embase databases were searched from inception up to September 2019 to identify all studies that compared the predictive performance of cystatin C- and/or creatinine-based eGFR in predicting the clearance of vancomycin. The prediction errors (PEs) (the value of eGFR equations minus vancomycin clearance) were quantified for each equation and were pooled using a random-effects model. The root mean squared errors were also quantified to provide a metric for imprecision.

RESULTS

This meta-analysis included evaluations of seven different cystatin C- and creatinine-based eGFR equations in total from 26 studies and 1,234 patients. The mean PE (MPE) for cystatin C-based eGFR was 4.378 mL min^-1 (95% confidence interval [CI], -29.425, 38.181), while the creatinine-based eGFR provided an MPE of 27.617 mL min^-1 (95% CI, 8.675, 46.560) in predicting clearance of vancomycin. This indicates the presence of unbiased results in vancomycin clearance prediction by the cystatin C-based eGFR equations. Meanwhile, creatinine-based eGFR equations demonstrated a statistically significant positive bias in vancomycin clearance prediction.

CONCLUSION

Cystatin C-based eGFR equations are better than creatinine-based eGFR equations in predicting the clearance of vancomycin. This suggests that utilising cystatin C-based eGFR equations could result in better accuracy and precision to predict vancomycin pharmacokinetic parameters.

Steady-state Pharmacokinetics of Vancomycin in Children Admitted to Pediatric Intensive Care Unit of a Tertiary Referral Center

Aims and objectives

Vancomycin is a drug of choice for various gram-positive bacterial (GPB) infections and is largely prescribed to pediatric intensive care unit (PICU) patients. Despite the different pathophysiology of these patients, limited data are available on pharmacokinetics of vancomycin. There are lack of data for critically ill Indian children; hence, study was conducted to assess the steady-state pharmacokinetics in children admitted to PICU.

Materials and methods

Twelve subjects (seven males, five females) aged 1–12 years were enrolled. Vancomycin (dose of 20 mg/kg per 8 hours) was infused for over 1 hour and steady-state pharmacokinetics was performed on day 3. Vancomycin concentrations were measured by the validated liquid chromatography mass spectrometry method. Pharmacokinetic parameters were calculated using Winnonlin (Version 6.3; Pharsight, St. Louis, MO).

Results

The steady-state mean C_ssmax was 40.94 μg/mL (±15.07), and mean AUC_{0–8 hours} was 124.15 μg/mL (±51.27). The mean t_1/2 was 4.82 hours (±2.71), Vd was 12.48 L (±4.43), and Cl was 2.08 mL/minute (±0.89). The mean AUC_0–24 among 12 subjects was 372.44 μg/mL (±153.82). Among 35 measured trough concentrations, 23 (65.71%) were below, 11 (31.43%) were within, and 1 (2.86%) was above the recommended range.

Conclusion

The pharmacokinetic parameters of vancomycin were comparable with previously reported studies. However, recommended trough levels (10–20 μg/mL) were not achievable with current recommended dosing of 60 mg/kg/day.

How to cite this article

Mali NB, Tullu MS, Wandalkar PP, Deshpande SP, Ingale VC, Deshmukh CT, et al. Steady-state Pharmacokinetics of Vancomycin in Children Admitted to Pediatric Intensive Care Unit of a Tertiary Referral Center. IJCCM 2019;23(11):497–502.

Single-dose and Steady-state Pharmacokinetics of Vancomycin in Critically Ill Patients Admitted to Medical Intensive Care Unit of India

Rationale

Vancomycin remains the standard of care for gram-positive bacterial infections, though there are significant developments in newer antibacterial agents. Efficacy can be improved by linking pharmacokinetic with pharmacodynamic principles, thus leading to optimum antibiotic exposure. There is scarcity of pharmacokinetic data in Indian intensive care unit (ICU) population.

Materials and methods

Fifteen subjects with suspected or proven gram-positive bacterial infection of either gender between 18 years and 65 years of age were enrolled. Vancomycin at the dose of 1 g every 12 hours was administered over 1-hour period and pharmacokinetic assessments performed on blood samples collected on days 1 and 3. Vancomycin concentrations were measured on validated liquid chromatography mass spectrometry method. Pharmacokinetic parameters were calculated using Winnonlin (Version 6.3; Pharsight, St. Louis, MO).

Results

The mean C_max, elimination half-life, AUC_0–12hours, volume of distribution, and clearance of single dose were 36.46 μg/mL (±14.87), 3.98 hours (±1.31), 113.51 μg/mL (±49.51), 52.01 L (±31.31), and 8.90 mL/minute (±3.29), respectively, and at steady state were 40.87 μg/mL (±19.29), 6.27 hours (±3.39), 147.94 μg/mL (±72.89), 56.39 L (±42.13), and 6.98 mL/minute (±4.48), respectively. The elimination half-life increased almost two-fold at steady state. The steady state mean AUC_0–24 was 295.89 µg/mL (±153.82). Out of 45 trough levels, 32 (71.11%) concentrations were below recommended range.

Conclusion

Recommended AUC_0–24hours and trough concentrations were not achieved in majority of patients with current dosing, suggesting reevaluation of current vancomycin dosing. Individualized treatment based on close monitoring of vancomycin serum concentrations in critically ill patients is imperative.

How to cite this article

Mali NB, Deshpande SP, Wandalkar PP, Gupta VA, Karnik ND, Gogtay NJ, et al. Single-dose and Steady-state Pharmacokinetics of Vancomycin in Critically Ill Patients Admitted to Medical Intensive Care Unit of India. IJCCM 2019;23(11):513–517.

Optimised dosing of vancomycin in critically ill Indigenous Australian patients with severe sepsis

Vancomycin is a commonly used antibiotic due to the high burden of methicillin-resistant <i>Staphylococcus aureus</i> infections. This study aimed to describe the pharmacokinetics (PK) of vancomycin in Australian Indigenous patients with severe sepsis, and advise an optimal dosing strategy. A population PK study was conducted in a remote Australian intensive care unit (ICU). Serial plasma samples were collected over one to two dosing intervals and assayed by validated chromatography. Concentration-time data collected were analysed using Pmetrics® software. The final population PK model was then used for Monte Carlo dosing simulations to determine optimal loading and intermittent maintenance doses. Fifteen Indigenous subjects were included for analysis with a median (interquartile range, IQR) age, weight and creatinine clearance (CrCL) of 43 (34-46) years, 73 (66-104) kg and 99 (56-139) ml/minute respectively. A two-compartment model described the data adequately. Vancomycin clearance (CL) and volume of distribution of the central compartment (Vc) were described by CrCL and patient weight respectively. Median (IQR) CL, Vc, distribution rate constants from central to peripheral, and from peripheral to central compartments were 4.6 (3.8-5.6) litres per hour, 25.4 (16.1-31.3) litres, 0.46 (0.28-0.52)/hour and 0.25 (0.12-0.37)/hour respectively. No significant interethnic PK differences were observed in comparison to published data. Therapeutic loading doses were significantly dependent on both weight and CrCL, whereas maintenance doses were dependent on CrCL. In the absence of severe renal impairment, initiation of maintenance dose eight hours post-loading dose achieved higher probability of target attainment at 24 hours. This is the first report of vancomycin PK in this patient group.

Measurement and Calculation of the Extracorporeal Elimination of Vancomycin During Continuous Venovenous Hemodiafiltration and Continuous Venovenous Hemofiltration in Critically Ill Patients

Six surgical intensive care patients with continuous renal replacement therapy and therapy with vancomycin entered the prospective clinical study. The first day the patients were treated with continuous venovenous hemodiafiltration (CVVHDF) and the second day with continuous venovenous hemofiltration (CVVH). Three patients received 500 mg and three patients received 1000 mg of vancomycin every 12 hours. Monoclonal fluorescence polarization immunoassay (AxSYM) of vancomycin levels was performed from serum and dialysate/ultrafiltrate (during CVVHDF) or ultrafiltrate (during CVVH). Blood flow was 90 ml/hr, substitution 1 L/hr predilution, dialysate flow 1 L/hr (CVVHDF). The extracorporeal elimination of vancomycin during CVVHDF and CVVH is nearly linear but shows wide interindividual variation. The extracorporeal clearance of vancomycin was 24.2 ± 3.1 ml/min during CVVHDF (total clearance 60.4 ±18.1 ml/min) and 14.5 ± 2.4 ml/min during CVVH (total clearance 50.2 ± 14.9 ml/min). Intraindividual comparison revealed a significantly higher elimination of vancomycin by CVVHDF (p < 0.028). Peak serum vancomycin levels in patients receiving vancomycin 1g/day were 24.7 ± 5.3 μg/ml (CVVH) and 23.1 ± 5.2 μg/ml (CVVHDF), and with 2 g/day were 33.5 ± 2.7 μg/ml (CVVH) and 27.3 ±4.1 μg/ml (CVVHDF). The daily excreted amount of vancomycin during CVVHDF (r2 = 0.950, p = 0.01) and CVVH (r2 = 0.947, p = 0.01) can be calculated from a vancomycin level in the ultrafiltrate/dialysate outlet (CVVHDF) or the ultrafiltrate (CVVH) 8 hours after dosing. The 8-hour concentration of vancomycin in the ultrafiltrate from CVVH (or ultrafiltrate/dialysate from CVVHDF) during continuous renal replacement therapy serves as a basis for predicting extracorporeal elimination within 24 hours for the individual patient. Since critically ill patients show wide interindividual and intraindividual differences in the volume of distribution, clearance, and elimination half-life of vancomycin during therapy, the estimation of serum levels remains a necessity.

The pharmacokinetics of vancomycin during the initial loading dose in patients with septic shock

OBJECTIVE

To characterize the pharmacokinetics (PK) of vancomycin in patients in the initial phase of septic shock.

METHODS

Twelve patients with septic shock received an intravenous infusion of vancomycin 30 mg/kg over 2 h. The vancomycin PK study was conducted during the first 12 h of the regimen. Serum vancomycin concentration-time data were analyzed using the standard model-independent analysis and the compartment model.

RESULTS

For the noncompartment analysis the mean values ± standard deviation (SD) of the estimated clearance and volume of distribution of vancomycin at steady state were 6.05±1.06 L/h and 78.73±21.78 L, respectively. For the compartmental analysis, the majority of vancomycin concentration-time profiles were best described by a two-compartment PK model. Thus, the two-compartmental first-order elimination model was used for the analysis. The mean ± SD of the total clearance (3.70±1.25 L/h) of vancomycin was higher than that obtained from patients without septic shock. In contrast, the volume of the central compartment (8.34±4.36 L) and volume of peripheral compartment (30.99±7.84 L) did not increase when compared with patients without septic shock.

CONCLUSION

The total clearance of vancomycin was increased in septic shock patients. However, the volume of the central compartment and peripheral compartment did not increase. Consequently, a loading dose of vancomycin should be considered in all patients with septic shock.

Comparison of the pharmacokinetics of vancomycin in neurosurgical and non-neurosurgical patients

Although vancomycin concentrations in neurosurgical patients tend to be lower following standard dosing compared with other patient populations, factors influencing vancomycin pharmacokinetics in neurosurgical patients are poorly understood. In this study, pharmacokinetic (PK) parameters in neurosurgical and non-neurosurgical patients were compared. Furthermore, factors influencing vancomycin PK alterations, including those known to augment renal clearance, were determined. Routine therapeutic drug monitoring data from neurosurgical and non-neurosurgical patients were retrospectively collected. Vancomycin PK parameters were estimated using non-linear mixed-effects modelling (NONMEM v.7.2.0); analyses were performed for the entire population and for neurosurgical patients only. Furthermore, the final models performed a bootstrap, visual predictive check and external validation. A total of 359 serum vancomycin concentration data variables from 132 patients were used to execute the PK modelling. Neurosurgical patient factor, the early phase of treatment, underlying liver cirrhosis, co-administration of a nephrotoxic drug and estimated creatinine clearance influenced vancomycin clearance (CL). However, other factors known to augment renal clearance did not affect vancomycin pharmacokinetics. Vancomycin CL was significantly higher in neurosurgical patients than in controls (0.104 ± 0.036 L/h/kg vs. 0.073 ± 0.042 L/h/kg; P <0.01). Augmented vancomycin CL should be considered when determining vancomycin dosages in neurosurgical patients.

Vancomycin pharmacokinetic models: informing the clinical management of drug-resistant bacterial infections

This review aims to critically evaluate the pharmacokinetic literature describing the use of vancomycin in the treatment of methicillin-resistant Staphylococcus aureus (MRSA) infections. Guidelines recommend that trough concentrations be used to guide vancomycin dosing for the treatment of MRSA infections; however, numerous in vitro, animal model and clinical studies have demonstrated that the therapeutic effectiveness of vancomycin is best described by the area under the concentration versus time curve (AUC) divided by the minimum inhibitory concentration (MIC) of the infecting organism (AUC/MIC). Among patients with lower respiratory tract infections, an AUC/MIC ≥400 was associated with a superior clinical and bacteriological response. Similarly, patients with MRSA bacteremia who achieved an Etest AUC/MIC ≥320 within 48 h were 50% less likely to experience treatment failure. For other patient populations and different clinical syndromes (e.g., children, the elderly, patients with osteomyelitis, etc.), pharmacokinetic/pharmacodynamic studies and prospective clinical trials are needed to establish appropriate therapeutic targets.

Optimizing antibiotic therapy of bacteremia and endocarditis due to staphylococci and enterococci: new insights and evidence from the literature

Gram-positive cocci are a well-recognised major cause of nosocomial infection worldwide. Bloodstream infections due to methicillin-resistant Staphylococcus aureus, methicillin-resistant coagulase-negative staphylococci, and multi-drug resistant enterococci are a cause of concern for physicians due to their related morbidity and mortality rates. Aim of this article is to review the current state of knowledge regarding the management of BSI caused by staphylococci and enterococci, including infective endocarditis, and to identify those factors that may help physicians to manage these infections appropriately. Moreover, we discuss the importance of an appropriate use of antimicrobial drugs, taking in consideration the in vitro activity, clinical efficacy data, pharmacokinetic/pharmacodynamic parameters, and potential side effects.

Can changes in renal function predict variations in β-lactam concentrations in septic patients?

This study investigated whether variations in creatinine clearance (CLCr) are correlated with changes in β-lactam concentrations or pharmacokinetics in septic patients. Data for 56 adult patients admitted to the ICU in whom routine therapeutic drug monitoring (TDM) of broad-spectrum β-lactams (ceftazidime, cefepime, piperacillin or meropenem) was performed were reviewed. Patients were included if they had at least two TDM during their ICU stay for the same antibiotic and were not concomitantly treated with any extracorporeal replacement therapy. Serum drug concentrations were measured by HPLC-UV. Antibiotic pharmacokinetics were calculated using a one-compartment model and the percentage of time spent above four times the MIC (%T>4×MIC) for Pseudomonas aeruginosa and the antibiotic clearance (ATB-CL) were obtained. CLCr was measured on the same day as the TDM using 24-h urine collection. The %T>4×MIC and ATB-CL were significantly correlated with CLCr at the first (r=-0.41, P=0.002; r=0.56, P<0.001, respectively) and second (r=-0.61, P<0.001; r=0.63, P<0.001, respectively) TDM. However, changes in ATB-CL were only weakly correlated with changes in CLCr (r=0.34, P=0.01). The proportion of patients with insufficient β-lactam concentrations at the first and second TDM were 39% and 30%, respectively, and increased proportionally to CLCr. Although CLCr was significantly correlated with concentrations and clearance of broad-spectrum β-lactams, changes in CLCr did not reliably predict variations in drug pharmacokinetics/pharmacodynamics. Routine TDM should be considered to adapt β-lactam doses in this setting.

Approaches for dosage individualisation in critically ill patients

INTRODUCTION

Pharmacokinetic variability in critically ill patients is the result of the overlapping of multiple pathophysiological and clinical factors. Unpredictable exposure from standard dosage regimens may influence the outcome of treatment. Therefore, strategies for dosage individualisation are recommended in this setting.

AREAS COVERED

The authors focus on several approaches for dosage individualisation that have been developed, ranging from the well-established therapeutic drug monitoring (TDM) up to the innovative application of pharmacogenomics criteria. Furthermore, the authors summarise the specific population pharmacokinetic models for different drugs developed for critically ill patients to improve the initial dosage selection and the Bayesian forecasting of serum concentrations. The authors also consider the use of Monte Carlo simulation for the selection of dosage strategies.

EXPERT OPINION

Pharmacokinetic/pharmacodynamics (PK/PD) modelling and dosage individualisation methods based on mathematical and statistical criteria will contribute in improving pharmacologic treatment in critically ill patients. Moreover, substantial effort will be necessary to integrate pharmacogenomics criteria into critical care practice. The lack of availability of target biomarkers for dosage adjustment emphasizes the value of TDM which allows a large part of treatment outcome variability to be controlled.

Initial vancomycin dosing recommendations for critically ill patients undergoing continuous venovenous hemodialysis

BACKGROUND

Delaying appropriate antimicrobial therapy for critically ill patients increases the risk of death. Currently, there are insufficient data to guide initial vancomycin dosing for patients undergoing continuous venovenous hemodialysis (CVVHD).

OBJECTIVE

To develop practical recommendations for initial dosing of vancomycin, based on the pharmacokinetics of this drug in critically ill patients undergoing CVVHD.

METHODS

A chart review was conducted for 24 critically ill adult patients who had undergone concurrent CVVHD and vancomycin therapy. Mean pharmacokinetic parameters were determined, along with practical recommendations for initial vancomycin dosing that targeted steady-state trough concentrations for patients receiving intermittent infusions and steady-state levels for those receiving continuous infusions between 15 and 20 mg/L. Monte Carlo simulation was used to develop the initial vancomycin dosing recommendations.

RESULTS

The mean (95% confidence interval) pharmacokinetic parameters for vancomycin (elimination rate constant 0.0315 [0.0254-0.0391], half-life 22.0 h [17.72-27.24 h], volume of distribution 0.96 L/kg [0.77-1.20 L/kg], and clearance 2.4 L/h [1.97-2.92 L/h]) indicated that initial intermittent IV dosing of 1.25-1.5 g q24h or 15 mg/kg q24h would be suitable. For continuous infusion, a 1.5-g IV loading dose followed by continuous infusion of 1-1.5 g IV over 24 h (42-62 mg/h) would be recommended. However, Monte Carlo simulation revealed that the probability of achieving desired concentrations between 15 and 20 mg/L with any of these initial regimens is low.

CONCLUSIONS

There was considerable variation in vancomycin pharmacokinetics in this patient population. The observations reported here raise concerns about the reliability of numerous empiric dosing recommendations derived from small pharmacokinetic studies in heterogeneous populations. Follow-up therapeutic drug monitoring is essential to ensure that concentrations remain within the target range.

Evaluation of the accuracy of a pharmacokinetic dosing program in predicting serum vancomycin concentrations in critically ill patients

BACKGROUND

Optimization of the timing of appropriate antibiotics is crucial to improve the management of patients in severe sepsis and septic shock. Vancomycin is commonly used empirically in cases of nosocomial infections in critically ill patients. Therefore, early optimization of vancomycin pharmacokinetics is likely to improve outcomes.

OBJECTIVE

To evaluate a pharmacokinetic program to predict serum vancomycin concentrations in accordance with administered dose, weight, height, and creatinine clearance in a critically ill population.

METHODS

We conducted a prospective observational single-center study in a 45-bed intensive care unit (ICU). All patients hospitalized in the ICU requiring intravenous treatment with vancomycin for a suspected infection were enrolled. The modalities of vancomycin therapy and the monitoring of serum concentrations were left to the discretion of the treating clinician. We compared the measured serum vancomycin concentrations with those predicted by the MM-USCPACK program and analyzed the factors influencing the prediction.

RESULTS

Fifty-four intravenous vancomycin courses were administered in 48 critically ill patients over the 3-month study. The precision was considered acceptable, based on a relative precision equal to 8.9% (interquartile range 3.5-18.9%) and the relative bias for all predictions was equal to -1.3%. Overall, 77.3% of predictions were within 20% of observed concentrations; factors correlating with a poorer prediction were a change in renal function, obesity, and the magnitude of organ dysfunction on initiation of vancomycin (expressed by a Systemic Organ Failure Assessment score >11).

CONCLUSIONS

The MM-USCPACK program is a useful and reliable tool for prediction of serum vancomycin concentrations in patients hospitalized in ICU and likely reflects the close monitoring of renal function in this setting. For some patients (more severely ill, obese, or significant change in renal function during vancomycin therapy), predictions were less precise.

Clearance of vancomycin during continuous infusion in Intensive Care Unit patients: correlation with measured and estimated creatinine clearance and serum cystatin C

Vancomycin (VAN) dosing requires adjustment to renal function, which is often estimated using the Cockcroft-Gault formula; however, its precision is poor in Intensive Care Unit (ICU) patients. VAN clearance (CL(Van)) during continuous infusion was prospectively determined in 25 ICU patients [14 male, 11 female; age range 31-82 years; body mass index (BMI) 16.5-41.5 kg/m²; Acute Physiology and Chronic Health Evaluation (APACHE) II score at admission 8-36; creatinine clearance 25-195 mL/min] and its correlation with measured creatinine clearance (CL(Crea)), estimated creatinine clearance using the Cockcroft-Gault formula (CL(CG)) and estimated glomerular filtration rate according to Hoek's formula based on serum cystatin C (GFR(Hoek)) was investigated. The correlation between CL(Van) and CL(Crea) was very good (r²=0.88), but it was rather poor with CL(CG) (r² = 0.37) and was acceptable with GFR(Hoek) (r² = 0.70). For VAN dose adjustments in ICU patients, determination of cystatin C may be an interesting and practical alternative to measured CL(Crea), whereas the Cockcroft-Gault formula should be used with caution.

Vancomycin dosing assessment in intensive care unit patients based on a population pharmacokinetic/pharmacodynamic simulation

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT * Despite the frequent use of vancomycin in intensive care unit (ICU) patients, few studies aimed at characterizing vancomycin population pharmacokinetics have been performed in this critical population. * Population pharmacokinetics coupled with pharmacodynamic analysis, in order to optimize drug exposure and hence antibacterial effectiveness, has been little applied in these specific patients. WHAT THIS STUDY ADDS * Our population model characterized the pharmacokinetic profile of vancomycin in adult ICU patients, higher distribution volume values (V) being observed when the patient's serum creatinine (Cr(Se)) was greater than 1 mg dl(-1). * Age and creatinine clearance (CL(cr)) were identified as the main covariates explaining the pharmacokinetic variability in vancomycin CL. * Our pharmacokinetic/pharmacodynamic (PK/PD) simulation should aid clinicians to select initial vancomycin doses that will maximize the rate of response in the ICU setting, taking into account the patient's age and renal function as well as the susceptibility of Staphylococcus aureus. AIM To estimate the vancomycin pharmacokinetic profile in adult ICU patients and to assess vancomycin dosages for increasing the likelihood of optimal exposure. METHODS Five hundred and sixty-nine concentration-time data from 191 patients were analysed using a population pharmacokinetic approach (NONMEN). External model evaluation was made in 46 additional patients. The 24 h area under the concentration-time curve (AUC(0,24 h)) was derived from the final model. Minimum inhibitory concentration (MIC) values for S. aureus were obtained from the EUCAST database. AUC(0,24 h) : MIC >/= 400 was considered as PK/PD efficacy index. The probability of different dosages attaining the target considering different strains of S. aureus and patient subgroups was estimated with Monte Carlo simulation. RESULTS Vancomycin CL showed a significant dependence on patient age and renal function whereas Cr(Se) > 1 mg dl(-1) increased V more than twofold. For our representative ICU patient, 61 years, 73 kg, Cr(Se)= 1.4 mg dl(-1), measured CL(Cr)= 74.7 ml min(-1), the estimated values were CL = 1.06 ml min(-1) kg(-1) and V= 2.04 l kg(-1). The cumulative fraction of response for a standard vancomycin dose (2 g day(-1)) was less than 25% for VISA strains, and 33% to 95% for susceptible S. aureus, depending on patient characteristics. CONCLUSIONS Simulations provide useful information regarding the initial assessment of vancomycin dosing, the conventional dosing regimen probably being suboptimal in adult ICU patients. A graphic approach provides the recommended dose for any selected probability of attaining the PK/PD efficacy target or to evaluate the cumulative fraction of response for any dosing regimen in this population.

Pharmacokinetics/pharmacodynamics of antibacterials in the Intensive Care Unit: setting appropriate dosing regimens

Patients admitted to Intensive Care Units (ICUs) are at very high risk of developing severe nosocomial infections. Consequently, antimicrobials are among the most important and commonly prescribed drugs in the management of these patients. Critically ill patients in ICUs include representatives of all age groups with a range of organ dysfunction related to severe acute illness that may complicate long-term illness. The range of organ dysfunction, together with drug interactions and other therapeutic interventions (e.g. haemodynamically active drugs and continuous renal replacement therapies), may strongly impact on antimicrobial pharmacokinetics in critically ill patients. In the last decade, it has become apparent that the intrinsic pharmacokinetic (PK) and pharmacodynamic (PD) properties are the major determinants of in vivo efficacy of antimicrobial agents. PK/PD parameters are essential in facilitating the translation of microbiological activity into clinical situations, ensuring a successful outcome. In this review, we analyse the typical patterns of antimicrobial activity and the corresponding PK/PD parameters, with a special focus on a PK/PD dosing approach of the antimicrobial agent classes commonly utilised in the ICU setting.

Vancomycin for treatment of invasive, multi-drug resistant Staphylococcus aureus infections

Staphylococcus aureus is a bacterial pathogen responsible for a variety of serious infections and is a frequent cause of nosocomial disease. During the last 60 years, S. aureus has developed increasing in vitro resistance to virtually all antimicrobials. In contrast, vancomycin has maintained a high degree of activity in vitro against this pathogen, although slight changes with in vitro activity could vastly change clinical activity. As a result, vancomycin has become the mainstay of therapy for invasive infections due to methicillin-resistant strains. However, clinical strains of S. aureus with intermediate resistance to vancomycin were reported in 1996, followed in 2002 with reports of isolates that were fully resistant. Although many authorities believe vancomycin remains the drug of choice for most staphylococcal-resistant infections, important issues surrounding its clinical application remain. These include the need for multiple daily dosing, intravenous administration, requirements for serum concentration monitoring, increasing resistance in vitro, modest efficacy rates and (less frequently) treatment-limiting adverse effects. This review addresses these important topics.

Pharmacokinetic/pharmacodynamic analysis of vancomycin in ICU patients

AIMS

To identify the variables affecting vancomycin pharmacokinetics in medical ICU patients and to evaluate the potential efficacy of dosage schedules by PK/PD analysis.

DESIGN

A retrospective pharmacokinetic analysis of serum levels obtained in routine vancomycin monitoring was performed.

SETTING

A 12-bed general ICU of a university teaching hospital.

PATIENTS

Forty-six vancomycin-treated ICU patients fitting the following criteria: over 18 years old; more than three concentration data per patient; absence of renal replacement support, cardiac surgery and neoplastic disorders.

INTERVENTIONS

Clinical information was collected from the patients' medical records. Details of vancomycin therapy, dosage and blood sampling times were obtained from pharmacokinetic reports. Population analysis were made by the standard two-stage approach.

MEASUREMENTS AND MAIN RESULTS

Vancomycin clearance and distribution volume were estimated individually assuming a one-compartment pharmacokinetic model. PK/PD analysis was performed by Monte Carlo simulation. In the ICU patients, higher Vd (nearly twice the quoted value of 0.72 l/kg) and different vancomycin clearance-creatinine clearance relationship were found. Renal function, the APACHE score, age and serum albumin accounted for more than 65% of drug clearance variability. Vancomycin standard dosages led to a 33% risk of not achieving the recommended AUC(24h)/MIC breakpoint for Staphylococcus aureus.

CONCLUSIONS

The population kinetics and PK/PD analyses based on Monte Carlo simulation procedures offer an excellent tool for selecting the therapeutic option with the highest probability of clinical success in ICU patients.

Population pharmacokinetic parameters of vancomycin in critically ill patients

BACKGROUND

Intensive care unit patients are a highly heterogeneous population. Accurate dosing for this population requires characterization of the appropriate pharmacokinetic parameters.

OBJECTIVE

To estimate population pharmacokinetic parameters of vancomycin (VAN) in adult critically ill patients and to establish the predictive performance of the resulting model.

PATIENTS AND METHOD

Fifty critically ill patients with suspected or documented infection with VAN-sensitive micro-organisms were included. Thirty patients and 234 serum concentration-time sets obtained during clinical routine monitoring were used to estimate the pharmacokinetic parameters (group A). An open bicompartimental model with intermittent intravenous administration was used to adjust the data. Data were evaluated using a nonlinear mixed effects model (nonmem software). Forty plasma concentration-time data sets from 20 patients were used for validation using the Bayesian method (group B).

RESULTS

There was a linear relationship between creatinine clearance (Cl(cr)) and VAN clearance (Cl(VAN)). The inclusion of the non-renal clearance (Cl(nr)) (intercept of Cl(VAN) vs. Cl(cr) relationship) improved the model significantly (Cl(nr) 17 mL/min). The volume of distribution seems to be larger than previously reported: volume of the central compartment (V(c)) was 0.41 L/kg and volume of the peripheral compartment was (V(p)), 1.32 L/kg. The mean error (bias) and mean absolute error (precision) for predicting subsequent peak concentrations were -2.16 and 9.28 mg/L and for trough concentrations, -0.22 and 3.87 mg/L respectively.

CONCLUSION

The use of population-specific pharmacokinetic parameters and Bayesian forecasting improves dosage-regimen design.

Evaluation of the estimation of midazolam concentrations and pharmacokinetic parameters in intensive care patients using a bayesian pharmacokinetic software (PKS) according to sparse sampling approach

The aim of the study was to assess the performance of a bayesian program (PKS System, Abbott) for predicting midazolam concentrations and pharmacokinetic parameters in intensive care patients by comparing the pharmacokinetic parameters estimated by PKS to those calculated according to rich data. The study involved 42 patients receiving midazolam infusion for two hours or for several days. The program was used to predict plasma midazolam concentrations after feedback of 1, 2 or 3 concentrations. High correlation between observed and estimated concentrations was shown (r(2) > 0.992). Mean prediction error, mean absolute prediction error and root mean squared error were low for the patients of the reference and validation groups. From two or three feedback concentrations, midazolam pharmacokinetic parameters estimated by PKS were statistically comparable with those obtained using a rich pharmacokinetic analysis (P > 0.05 paired Wilcoxon test). Thus, PKS is useful for predicting midazolam concentrations and pharmacokinetic parameters when at least two feedback concentrations are known. This software seems to be appropriate for providing significant help to the clinician for midazolam dosage adjustment, according to midazolam concentrations and clinical sedation.

Bayesian forecasting and prediction of tacrolimus concentrations in pediatric liver and adult renal transplant recipients

AIM

To test the predictive capacity of two recently derived population pharmacokinetic models and the usefulness of Bayesian forecasting to predict tacrolimus blood concentrations in pediatric liver and adult kidney transplant recipients.

MATERIALS AND METHODS

New databases were added to the Abbottbase PKS (Bayesian dosage prediction) program to incorporate the population pharmacokinetic models developed for tacrolimus. Two independent populations of transplant recipients were used to predict tacrolimus trough concentrations. Pharmacokinetic, demographic, and covariate data were collected from patient records. Different time weighting factors were tested (1, 1.005, 1.01) and the influence of excluding data collected in the first 5 days post-transplant examined. Concentrations were predicted until the 10th tacrolimus measurement. Actual tacrolimus concentrations were compared with those predicted by the PKS program and bias and precision determined.

RESULTS

Tacrolimus concentrations predicted by the PKS program were, on average, unbiased for the pediatric liver population, but were over-predicted (9%) for the adult renal population. In both populations predictions were not precise (imprecision ranged from 39 to 50%).

CONCLUSIONS

Due to the imprecision seen in this study, these models could not be used in clinical practice in the immediate post-transplant period. Poor precision may be due to reliance on routine drug monitoring data alone, difficulties with expression of covariates in continuous modeling relationships in the PKS program, lack of accurate quantitative measures of liver function, or large, random intraindividual variability in the bioavailability of tacrolimus.

Evaluation of predictability for vancomycin dosage regimens by the Bayesian method with Japanese population pharmacokinetic parameters

The predictability of serum vancomycin (VCM) concentrations by means of the Bayesian method was evaluated to establish whether the method can be used to select safe and effective VCM treatment regimens for individual patients. Serum VCM concentrations at the trough and 2 h after the end of infusion (peak) were measured. Pharmacokinetic parameters were calculated for VCM dosage regimens based on a two-compartment model with the Bayesian method, using the Japanese population pharmacokinetic parameters estimated by Yasuhara et al. (1998). The predictive performance for serum VCM concentrations and the dosage regimens were analyzed using two points of serum VCM concentration in 41 patients whose serum creatinine and age were in the ranges of 0.4-4.6 mg/dl and 24-92 years, respectively. Although the predicted values for trough and peak VCM concentrations were slightly lower than measured VCM concentrations, the predictive performance was generally good. There were no differences among the groups classified by serum creatinine or age. An examination of predicted data that differed markedly from the measured serum VCM concentrations indicated that a larger difference in volume of distribution at the steady state (Vdss) calculated from serum VCM concentrations at the beginning and revision of dosage regimens resulted in a poorer correlation of predicted values and measured values. This finding indicates that therapeutic drug monitoring should be conducted frequently, and the dosage regimen revised accordingly, in the case of patients who may have a change of Vdss of VCM, for example, due to a complication such as heart failure or edema.

Pharmacokinetics of a new parenteral oligosaccharide antibiotic, SCH27899 (Ziracin), in healthy subjects

The pharmacokinetic properties of an everninomicin antibiotic (SCH27899; Ziracin) were studied with healthy Japanese male volunteers by single (1, 3, 6, and 9 mg/kg of body weight) and multiple 60-min intravenous infusions (3, 6, and 9 mg/kg once daily for 10 consecutive days following a 2-day interval after the initial dose). At single doses the peak serum concentration and the area under the serum concentration-time curve linearly increased with the dose. While total body clearance (CL; 31.2 to 45.6 ml/kg/h) and percent cumulative urinary recovery as unchanged drug (4.9 to 7.1%) were rather constant irrespective of doses, the terminal half-life of gamma phase (t(1/2 gamma); 14.2 to 19.6 h) were slightly prolonged at the higher two doses compared with the lower two doses. With repeated doses of SCH27899, a statistically significant decrease and increase were found in CL and t(1/2 gamma) of about 36 and 21%, respectively, although these changes may be clinically irrelevant. The most commonly reported adverse events were local reactions such as erythema, pain, and palpable venous cord of mild to moderate degree around the injection site, which could be managed by changing the injection sites.

[Glycopeptides]

OBJECTIVES

To review pharmacology, pharmacokinetic and therapeutic use of glycopeptides in intensive care units.

DATA SOURCES

Extraction from Medline database of French and English articles on glycopeptides and search along with major review articles.

DATA SELECTION

The collected articles were reviewed and selected according to their quality and originality. The more recent data were selected.

DATA SYNTHESIS

Glycopeptides are bactericidal antibiotics which are only active against Gram positive species acting by inhibiting peptidoglycan synthesis. They had been in clinical use for almost 30 years without high-level resistance underlining. For ten years, there have been disturbing reports of first, resistance to vancomycin in enterococcal species and more recently in strains of Staphylococcus aureus by complex and large mechanisms of action. This new resistances may lead to a therapeutic impasse and a fatal issue for infected patients. The only response to this situation is the respect of prescription rules and the careful use of antibiotics.

CONCLUSION

Considering their spectrum, glycopeptides are an antibiotic family which importance is fundamental to treat infected patients of intensive care units. Staff members of intensive care units are responsible for their good use.