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In the intensive care unit (ICU), infection-related mortality is high. Although adequate antibiotic treatment is essential in infections, beta-lactam target non-attainment occurs in up to 45% of ICU patients, which is associated with a lower likelihood of clinical success. To optimize antibiotic treatment, we aimed to develop beta-lactam target non-attainment prediction models in ICU patients. Patients from two multicenter studies were included, with intravenous intermittent beta-lactam antibiotics administered and blood samples drawn within 12–36 h after antibiotic initiation. Beta-lactam target non-attainment models were developed and validated using random forest (RF), logistic regression (LR), and naïve Bayes (NB) models from 376 patients. External validation was performed on 150 ICU patients. We assessed performance by measuring discrimination, calibration, and net benefit at the default threshold probability of 0.20. Age, sex, serum creatinine, and type of beta-lactam antibiotic were found to be predictive of beta-lactam target non-attainment. In the external validation, the RF, LR, and NB models confirmed good discrimination with an area under the curve of 0.79 [95% CI 0.72–0.86], 0.80 [95% CI 0.73–0.87], and 0.75 [95% CI 0.67–0.82], respectively, and net benefit in the RF and LR models. We developed prediction models for beta-lactam target non-attainment within 12–36 h after antibiotic initiation in ICU patients. These online-accessible models use readily available patient variables and help optimize antibiotic treatment. The RF and LR models showed the best performance among the three models tested. [ABSTRACT FROM AUTHOR]

Effective dosing of isavuconazole in patients supported by extracorporeal membrane oxygenation (ECMO) is important due to the role of isavuconazole as a first-line treatment in patients with influenza- and COVID-19-associated pulmonary aspergillosis. To date, robust pharmacokinetic data in patients supported by ECMO are limited. Therefore, it is unknown whether ECMO independently impacts isavuconazole exposure. We measured isavuconazole plasma concentrations in two patients supported by ECMO and estimated individual pharmacokinetic parameters using non-compartmental analysis and two previously published population pharmacokinetic models. Furthermore, a narrative literature review on isavuconazole exposure in adult patients receiving ECMO was performed. The 24 h areas under the concentration–time curve and trough concentrations of isavuconazole were lower in both patients compared with exposure values published before. In the literature, highly variable isavuconazole concentrations have been documented in patients with ECMO support. The independent effect of ECMO versus critical illness itself on isavuconazole exposure cannot be deduced from our and previously published (case) reports. Pending additional data, therapeutic drug monitoring is recommended in critically ill patients, regardless of ECMO support. [ABSTRACT FROM AUTHOR]

The ARC predictor is a prediction model for augmented renal clearance (ARC) on the next intensive care unit (ICU) day that showed good performance in a general ICU setting. In this study, we performed a retrospective external validation of the ARC predictor in critically ill coronavirus disease 19 (COVID-19) patients admitted to the ICU of the University Hospitals Leuven from February 2020 to January 2021. All patient-days that had serum creatinine levels available and measured creatinine clearance on the next ICU day were enrolled. The performance of the ARC predictor was evaluated using discrimination, calibration, and decision curves. A total of 120 patients (1064 patient-days) were included, and ARC was found in 57 (47.5%) patients, corresponding to 246 (23.1%) patient-days. The ARC predictor demonstrated good discrimination and calibration (AUROC of 0.86, calibration slope of 1.18, and calibration-in-the-large of 0.14) and a wide clinical-usefulness range. At the default classification threshold of 20% in the original study, the sensitivity and specificity were 72% and 81%, respectively. The ARC predictor is able to accurately predict ARC in critically ill COVID-19 patients. These results support the potential of the ARC predictor to optimize renally cleared drug dosages in this specific ICU population. Investigation of dosing regimen improvement was not included in this study and remains a challenge for future studies. [ABSTRACT FROM AUTHOR]

In the current Special Issue on "Therapeutic drug monitoring of antimicrobials", several research articles and reviews have been published that support TDM-based antimicrobial dose optimization strategies in special patient populations. TDM results can be used as such, or they can be integrated in dosing nomograms or dosing software to optimize antimicrobial exposure, and ultimately, clinical outcome. Keywords: therapeutic drug monitoring; precision dosing; antibiotic; antifungal; antiviral; dose optimization EN therapeutic drug monitoring precision dosing antibiotic antifungal antiviral dose optimization 815 3 06/28/22 20220601 NES 220601 A recent guideline [[1]] and position paper [[2]] defined dose optimization as a priority for antimicrobial research in special patient populations, such as critically ill patients. [Extracted from the article]

Children show important developmental and maturational changes, which may contribute greatly to pharmacokinetic (PK) variability observed in pediatric patients. These PK alterations are further enhanced by disease-related, non-maturational factors. Specific to the intensive care setting, such factors include critical illness, inflammatory status, augmented renal clearance (ARC), as well as therapeutic interventions (e.g., extracorporeal organ support systems or whole-body hypothermia [WBH]). This narrative review illustrates the relevance of both maturational and non-maturational changes in absorption, distribution, metabolism, and excretion (ADME) applied to antibiotics. It hereby provides a focused assessment of the available literature on the impact of critical illness—in general, and in specific subpopulations (ARC, extracorporeal organ support systems, WBH)—on PK and potential underexposure in children and neonates. Overall, literature discussing antibiotic PK alterations in pediatric intensive care is scarce. Most studies describe antibiotics commonly monitored in clinical practice such as vancomycin and aminoglycosides. Because of the large PK variability, therapeutic drug monitoring, further extended to other antibiotics, and integration of model-informed precision dosing in clinical practice are suggested to optimise antibiotic dose and exposure in each newborn, infant, or child during intensive care. [ABSTRACT FROM AUTHOR]

Background: Voriconazole is an antifungal drug used as one of the first-line treatments for invasive aspergillosis. This drug is extensively metabolized, predominantly via cytochrome P450 enzymes. An interaction between flucloxacillin and voriconazole, leading to subtherapeutic voriconazole concentrations, has previously been reported. We aimed to demonstrate that flucloxacillin independently influences voriconazole exposure. Methods: Patients from three Belgian hospitals, treated with a combination of voriconazole and flucloxacillin, were included in this retrospective study. Voriconazole concentrations were collected both in a timeframe with and without flucloxacillin co-treatment. Multivariate analyses were performed to study the independent effect of flucloxacillin treatment on voriconazole exposure and the possible influence of the flucloxacillin dose. Results: Thirty-three patients were included in this study and 145 trough concentrations (51 with, and 94 without concomitant flucloxacillin treatment) were analyzed. The median (IQR) voriconazole trough concentration sampled during flucloxacillin co-treatment was 0.5 (0–1.8) mg/L, whereas samples without flucloxacillin co-treatment had a median (IQR) voriconazole trough concentration of 3.5 (1.7–5.1) mg/L (p = 0.002), while receiving similar voriconazole doses. Subtherapeutic concentrations (<1 mg/L) were observed in 69% and 7% of the samples with flucloxacillin co-treatment versus samples without flucloxacillin co-treatment, respectively. Conclusion: This study shows that flucloxacillin co-treatment independently decreases voriconazole exposure. Caution is needed when these two drugs are administered simultaneously. [ABSTRACT FROM AUTHOR]

The impact of ceftriaxone pharmacokinetic alterations on protein binding and PK/PD target attainment still remains unclear. We evaluated pharmacokinetic/pharmacodynamic (PK/PD) target attainment of unbound ceftriaxone in critically ill patients with severe community-acquired pneumonia (CAP). Besides, we evaluated the accuracy of predicted vs. measured unbound ceftriaxone concentrations, and its impact on PK/PD target attainment. A prospective observational cohort study was carried out in adult patients admitted to the intensive care unit with severe CAP. Ceftriaxone 2 g q24h intermittent infusion was administered to all patients. Successful PK/PD target attainment was defined as unbound trough concentrations above 1 or 4 mg/L throughout the whole dosing interval. Acceptable overall PK/PD target attainment was defined as successful target attainment in ≥90% of all dosing intervals. Measured unbound ceftriaxone concentrations (CEFu) were compared to unbound concentrations predicted from various protein binding models. Thirty-one patients were included. The 1 mg/L and 4 mg/L targets were reached in 26/32 (81%) and 15/32 (47%) trough samples, respectively. Increased renal function was associated with the failure to attain both PK/PD targets. Unbound ceftriaxone concentrations predicted by the protein binding model developed in the present study showed acceptable bias and precision and had no major impact on PK/PD target attainment. We showed suboptimal (i.e., <90%) unbound ceftriaxone PK/PD target attainment when using a standard 2 g q24h dosing regimen in critically ill patients with severe CAP. Renal function was the major driver for the failure to attain the predefined targets, in accordance with results found in general and septic ICU patients. Interestingly, CEFu was reliably predicted from CEFt without major impact on clinical decisions regarding PK/PD target attainment. This suggests that, when carefully selecting a protein binding model, CEFu does not need to be measured. As a result, the turn-around time and cost for ceftriaxone quantification can be substantially reduced. [ABSTRACT FROM AUTHOR]

There are concerns about the stability of meropenem in plasma samples, even when frozen at −20 °C. Previous smaller studies suggested significant degradation of meropenem at −20 °C after 3–20 days. However, in several recent clinical studies, meropenem plasma samples were still stored at −20 °C, or the storage temperature and/or time were not mentioned in the paper. The aim of this study was to describe and model meropenem degradation in human plasma at −20 °C over 1 year. Stability of meropenem in human plasma at −20 °C was investigated at seven concentrations (0.44, 4.38, 17.5, 35.1, 52.6, 70.1, and 87.6 mg/L) representative for the range of relevant concentrations encountered in clinical practice. For each concentration, samples were stored for 0, 7, 14, 21, 28, 42, 56, 70, 84, 112, 140, 168, 196, 224, 252, 280, 308, 336, and 364 days at −20 °C before being transferred to −80 °C until analysis. Degradation was modeled using polynomial regression analysis and artificial neural network (ANN). Meropenem showed significant degradation over time in human plasma when stored at −20 °C. Degradation was present over the whole concentration range and increased with higher concentrations until a concentration of 35.1 mg/L. Both models showed accurate prediction of meropenem degradation. In conclusion, this study provides detailed insights into the concentration-dependent degradation of meropenem in human plasma stored at −20 °C over 1 year. Meropenem in human plasma is shown to be stable at least up to approximately 80 days when stored at −20 °C. The polynomial model allows calculating original meropenem concentrations in samples stored for a known period of time at −20 °C. [ABSTRACT FROM AUTHOR]