Purpose: CytoSorb® (CS) adsorbent is a hemoadsorption filter for extracorporeal blood purification often integrated into continuous kidney replacement therapy (CKRT). It is primarily used in critically ill patients with sepsis and related conditions, including cytokine storms and systemic inflammatory responses. Up to now, there is no evidence nor recommendation for the use of CS filters in sepsis (22). There is limited clinical data on the effect of CS on the plasma concentrations of beta-lactams. We aimed to evaluate the statistical and clinical impact of CS in a post-filter CKRT-CS setting on the plasma concentrations of the antibiotics meropenem and piperacillin in critically ill patients. Methods: Patients admitted to the intensive care unit (ICU) who received a prolonged infusion of piperacillin or meropenem with CS-combined CKRT were included in this retrospective analysis. TDM (therapeutic drug monitoring) plasma blood samples were collected at three different points. The differences in antibiotic concentrations between Pre, Intra, and Post were statistically compared to evaluate the total and isolated contributions of CKRT and CS to antibiotic removal. CS, CKRT and combined clearance (CL) values were calculated. The hypothesis was that the CS filter would have no clinically relevant impact on antibiotic levels. Results: 207 TDM samples were taken from 24 critically ill patients requiring beta-lactam antibiotics. Among these, 129 were meropenem samples, and 78 were piperacillin samples. A decrease in both antibiotic levels was observed between Pre and Intra, and Pre and Post, and the median relative difference between was >15% (meropenem: Pre–Intra 34.8%, Pre–Post 35.8%; piperacillin: Pre–Intra 41.1%, Pre–Post 34.7%), indicating a statistically and clinically significant effect of CKRT on both antibiotic exposures. No significant difference was observed between Intra and Post indicating no clinically relevant drug removal via the CS filter. Changes in CL attributed to CS were minimal, with combined CL differing by ≤8.60% compared to CKRT clearance. Conclusion: The application of CS does not appear to significantly affect plasma concentrations of meropenem and piperacillin in critically ill patients.

Background: A novel fixed combination of aztreonam (ATM) and avibactam (AVI) offers promising potential to treat infections with carbapenem-resistant Enterobacterales (CRE) producing metallo-β-lactamases (MBL). This study aimed to assess the accuracy of population pharmacokinetic (PK) models for ATM-AVI in predicting in vivo concentrations in a critically ill patient with CRE infection during its first clinical use. Methods: A 70-year-old male with septic shock due to hospital-acquired pneumonia (HAP) caused by MBL-producing Klebsiella pneumoniae was treated with ATM-AVI. Trough and peak serum concentrations (32 samples over 7 days) were measured using liquid chromatography–tandem mass spectrometry (LC-MS/MS). Population PK models were used to simulate complete concentration–time profiles. Bland–Altman analysis assessed model performance by comparing predicted and measured concentrations. Results: Median ATM trough concentrations (18.4 mg/L) remained above the minimum inhibitory concentration (MIC) of 1 mg/L for the pathogen. The Bland–Altman analysis demonstrated reasonable agreement between predicted and observed concentrations, with a relative bias (rBias) of −50.5% for ATM and −14.4% for AVI. ATM-AVI ratios remained stable. Clinical improvement and sterile blood cultures within 12 days led to intensive care unit (ICU) discharge. Conclusions: Population PK models for ATM-AVI accurately predicted in vivo concentrations in a severely ill patient with HAP. Therapeutic drug monitoring (TDM) with PK modeling ensured optimal antimicrobial exposure and contributed to clinical recovery.

The drug concentrations targeted in meropenem and piperacillin/tazobactam therapy also depend on the susceptibility of the pathogen. Yet, the pathogen is often unknown, and antibiotic therapy is guided by empirical targets. To reliably achieve the targeted concentrations, dosing needs to be adjusted for renal function. We aimed to evaluate a meropenem and piperacillin/tazobactam monitoring program in intensive care unit (ICU) patients by assessing (i) the adequacy of locally selected empirical targets, (ii) if dosing is adequately adjusted for renal function and individual target, and (iii) if dosing is adjusted in target attainment (TA) failure. In a prospective, observational clinical trial of drug concentrations, relevant patient characteristics and microbiological data (pathogen, minimum inhibitory concentration (MIC)) for patients receiving meropenem or piperacillin/tazobactam treatment were collected. If the MIC value was available, a target range of 1–5 × MIC was selected for minimum drug concentrations of both drugs. If the MIC value was not available, 8–40 mg/L and 16–80 mg/L were selected as empirical target ranges for meropenem and piperacillin, respectively. A total of 356 meropenem and 216 piperacillin samples were collected from 108 and 96 ICU patients, respectively. The vast majority of observed MIC values was lower than the empirical target (meropenem: 90.0%, piperacillin: 93.9%), suggesting empirical target value reductions. TA was found to be low (meropenem: 35.7%, piperacillin 50.5%) with the lowest TA for severely impaired renal function (meropenem: 13.9%, piperacillin: 29.2%), and observed drug concentrations did not significantly differ between patients with different targets, indicating dosing was not adequately adjusted for renal function or target. Dosing adjustments were rare for both drugs (meropenem: 6.13%, piperacillin: 4.78%) and for meropenem irrespective of TA, revealing that concentration monitoring alone was insufficient to guide dosing adjustment. Empirical targets should regularly be assessed and adjusted based on local susceptibility data. To improve TA, scientific knowledge should be translated into easy-to-use dosing strategies guiding antibiotic dosing.

Background and objectives: The MIC, determined in vitro using a fixed tazobactam concentration, is used as basis for the pharmacokinetic/pharmacodynamic (PK/PD) index of piperacillin/tazobactam. The β-lactamase inhibitor (BLI) concentration-dependent MIC (MICcBLI) represents a promising alternative PD metric accounting for varying tazobactam concentrations observed in vivo. The aim was to investigate how the effect of varying in vivo tazobactam concentrations can be incorporated through the in vitro MICcBLI as a PD metric to assess the probability of three piperacillin/tazobactam dosing regimens to achieve predefined target values. Methods: The MICcBLI for six isolates was evaluated as function of tazobactam concentrations. Two nonlinear mixed-effects PK models for piperacillin and tazobactam were developed based on data from 44 critically ill patients. Probability of target attainment (PTA) analysis was performed, and PTA values for the PK/PD targets 100% fT > MIC and 100% fT > MICcBLI were assessed. Results: The susceptibility against piperacillin was dependent on the tazobactam concentration for all isolates. A two-compartment PK model with inter-occasion variability on clearance (CL) and inter-individual variability on CL and both volumes, with creatinine clearance as a covariate on CL, described the PK of piperacillin and tazobactam best. The PTA analysis revealed differences between the isolates, three infusion types and the two metrics. Conclusions: By adopting this framework, dosing optimization can be approached to provide support for the rational design of piperacillin/tazobactam dosing regimens and other β-lactam/β-lactamase combinations. The shift from the conventional MIC to a β-lactamase inhibitor concentration-dependent metric clearly improved the knowledge of the susceptibility of a pathogen against piperacillin/tazobactam.

Purpose An increasing number of critically ill patients receive slow extended daily dialysis (SLEDD) due to their pathophysiology while suffering from sepsis, necessitating effective and safe antibiotic therapy. Although SLEDD reduces meropenem exposure and increases treatment failure risk, effective and safe dosing regimens are unclear. We aimed to identify optimised meropenem dosing strategies for critically ill SLEDD patients through population pharmacokinetic (PK) modelling and PK/pharmacodynamic (PD)-based probability of target attainment (PTA) analysis. Methods Clinical data from a prospective study involving critically ill SLEDD patients receiving meropenem were monitored through routine therapeutic drug monitoring. A total of 178 blood samples from 13 patients (median 14 samples per patient) were analysed. A PK model was developed and utilised to evaluate 24 clinically relevant dosing regimens during SLEDD therapy (7-h on-SLEDD periods q24h) in PTA analyses. The PK/PD target window of minimum meropenem concentration between 8 mg/L (P. aeruginosa; R-breakpoint) and 44.45 mg/L (toxicity threshold) was used. Results A one-compartment PK model with linear elimination and total clearance (CL) split into renal (CL_REN; 45%) and SLEDD-associated (55%) CL well characterised the SLEDD data. Creatinine clearance (urine-collected; CLCR_urine) was identified as significant factor on CL_REN. Continuous infusions, specifically 2 g q24h for CLCR_urine 0–25 mL/min and 3 g q24h for CLCR_urine 25–40 mL/min, showed the highest PTA being effective and safe during SLEDD therapy. A comprehensive dosing nomogram was developed. Conclusion Our easy-to-use dosing nomogram presents a promising tool in optimising meropenem dosing regimens for critically ill SLEDD patients considering their kidney function in clinical practice. Trial registration Clinicaltrials.gov NCT03985605. Registered 14 June 2019. https://classic.clinicaltrials.gov/ct2/show/study/NCT03985605 Graphical abstract