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Effective antibiotic dosing is vital for therapeutic success in critically ill patients. This work aimed to develop an algorithm to identify appropriate meropenem dosing in critically ill patients. Population pharma-cokinetic (PK) modelling was performed in NONMEM (R) 7.3 based on densely sampled meropenem serum samples (n(patients) = 48; n(samples) =1376) and included a systematic analysis of 27 pre-selected covariates to identify factors influencing meropenem exposure. Using Monte Carlo simulations newly considering the uncertainty of PK parameter estimates, standard meropenem dosing was evaluated with respect to attainment of the pharmacokinetic/pharmacodynamic (PK/PD) target and was compared with alternative infusion regimens (short-term, prolonged, continuous; daily dose, 2000-6000 mg). Subsequently, a dosing algorithm was developed to identify appropriate dosing regimens. The two-compartment population PK model included three factors influencing meropenem pharmacokinetics: the Cockcroft-Gault creatinine clearance (CLCRCG ) on meropenem clearance; and body weight and albumin on the central and peripheral volume of distribution, respectively; of these, only CLCRCG was identified as a vital influencing factor on PK/PD target attainment. A three-level dosing algorithm was developed (considering PK parameter uncertainty), suggesting dosing regimens depending on renal function and the level (L) of knowledge about the infecting pathogen (L1, pathogen unknown; L2, pathogen known; L3((-MIC)), pathogen and susceptibility known; L3((+MIC)), MIC known). Whereas patients with higher CLCRCG and lower pathogen susceptibility required mainly intensified dosing regimens, lower than standard doses appeared sufficient for highly susceptible pathogens. In conclusion, a versatile meropenem dosing algorithm for critically ill patients is proposed, indicating appropriate dosing regimens based on patient- and pathogen-specific information. (C) 2019 Published by Elsevier B.V.
Background: Severe bacterial infections remain a major challenge in intensive care units because of their high prevalence and mortality. Adequate antibiotic exposure has been associated with clinical success in critically ill patients. The objective of this study was to investigate the target attainment of standard meropenem dosing in a heterogeneous critically ill population, to quantify the impact of the full renal function spectrum on meropenem exposure and target attainment, and ultimately to translate the findings into a tool for practical application. Methods: A prospective observational single-centre study was performed with critically ill patients with severe infections receiving standard dosing of meropenem. Serial blood samples were drawn over 4 study days to determine meropenem serum concentrations. Renal function was assessed by creatinine clearance according to the Cockcroft and Gault equation (CLCRCG). Variability in meropenem serum concentrations was quantified at the middle and end of each monitored dosing interval. The attainment of two pharmacokinetic/pharmacodynamic targets (100% T->MIC, 50% T->4xMIC) was evaluated for minimum inhibitory concentration (MIC) values of 2 mg/L and 8 mg/L and standard meropenem dosing (1000 mg, 30-minute infusion, every 8 h). Furthermore, we assessed the impact of CLCRCG on meropenem concentrations and target attainment and developed a tool for risk assessment of target non-attainment. Results: Large inter-and intra-patient variability in meropenem concentrations was observed in the critically ill population (n = 48). Attainment of the target 100% T->MIC was merely 48.4% and 20.6%, given MIC values of 2 mg/L and 8 mg/L, respectively, and similar for the target 50% T->4xMIC. A hyperbolic relationship between CLCRCG (25-255 ml/minute) and meropenem serum concentrations at the end of the dosing interval (C-8h) was derived. For infections with pathogens of MIC 2 mg/L, mild renal impairment up to augmented renal function was identified as a risk factor for target non-attainment (for MIC 8 mg/L, additionally, moderate renal impairment). Conclusions: The investigated standard meropenem dosing regimen appeared to result in insufficient meropenem exposure in a considerable fraction of critically ill patients. An easy-and free-to-use tool (the MeroRisk Calculator) for assessing the risk of target non-attainment for a given renal function and MIC value was developed.
Development of a tool to identify intensive care patients at risk of meropenem therapy failure
(2018)
Meropenem is one of the most frequently used antibiotics to treat life-threatening infections in critically ill patients.
This study aimed to develop a meropenem dosing algorithm for the treatment of Gram-negative infections based on intensive care unit (ICU)-specific resistance data. Antimicrobial susceptibility testing of Gram-negative bacteria obtained from critically ill patients was carried out from 2016 to 2020 at a tertiary care hospital.
Based on the observed MIC distribution, stochastic simulations (n = 1,000) of an evaluated pharmacokinetic meropenem model, and a defined pharmacokinetic/pharmacodynamic target (100%T->4xMIC while minimum concentrations were <44.5 mg/L), dosing recommendations for patients with varying renal function were derived.
Pathogen-specific MIC distributions were used to calculate the cumulative fraction of response (CFR), and the overall MIC distribution was used to calculate the local pathogen-independent mean fraction of response (LPIFR) for the investigated dosing regimens.
A CFR/LPIFR of >90% was considered adequate. The observed MIC distribution significantly differed from the EUCAST database. Based on the 6,520 MIC values included, a three-level dosing algorithm was developed.
If the pathogen causing the infection is unknown (level 1), known (level 2), known to be neither Pseudomonas aeruginosa nor Acinetobacrer baumannii, or classified as susceptible (level 3), a continuous infusion of 1.5 g daily reached sufficient target attainment independent of renal function.
In all other cases, dosing needs to be adjusted based on renal function. ICU-specific susceptibility data should be assessed regularly and integrated into dosing decisions. The presented workflow may serve as a blueprint for other antimicrobial settings.
Background:
Hemadsorption of cytokines is used in critically ill patients with sepsis or septic shock. Concerns have been raised that the cytokine adsorber CytoSorb (R) unintentionally adsorbs vancomycin. This study aimed to quantify vancomycin elimination by CytoSorb (R) .
Methods:
Critically ill patients with sepsis or septic shock receiving continuous renal replacement therapy and CytoSorb (R) treatment during a prospective observational study were included in the analysis. Vancomycin pharmacokinetics was characterized using population pharmacokinetic modeling. Adsorption of vancomycin by the CytoSorb (R) was investigated as linear or saturable process. The final model was used to derive dosing recommendations based on stochastic simulations.
Results:
20 CytoSorb (R) treatments in 7 patients (160 serum samples/24 during CytoSorb (R)-treatment, all continuous infusion) were included in the study. A classical one-compartment model, including effluent flow rate of the continuous hemodialysis as linear covariate on clearance, best described the measured concentrations (without CytoSorb (R)). Significant adsorption with a linear decrease during CytoSorb (R) treatment was identified (p <0.0001) and revealed a maximum increase in vancomycin clearance of 291% (initially after CytoSorb (R) installation) and a maximum adsorption capacity of 572 mg. For a representative patient of our cohort a reduction of the area under the curve (AUC) by 93 mg/L*24 h during CytoSorb (R) treatment was observed. The additional administration of 500 mg vancomycin over 2 h during CytoSorb (R) attenuated the effect and revealed a negligible reduction of the AUC by 4 mg/L*24h.
Conclusion:
We recommend the infusion of 500 mg vancomycin over 2 h during CytoSorb (R) treatment to avoid subtherapeutic concentrations.