Stability of 10 Beta-Lactam Antibiotics in Human Plasma at Different Storage Conditions

BACKGROUND: Recently, several studies have assessed the effects of therapeutic drug monitoring of frequently prescribed beta-lactam antibiotics, for which they were quantified in human plasma samples. Beta-lactams are considered unstable, leading to extra challenges in quantification. Therefore, to ensure sample stability and minimize sample degradation before analysis, stability studies are crucial. This study investigated the stability of 10 frequently used beta-lactam antibiotics in human plasma at relevant storage conditions for clinical use. METHODS: Amoxicillin, benzylpenicillin, cefotaxime, ceftazidime, ceftriaxone, cefuroxime, flucloxacillin, imipenem, meropenem, and piperacillin were analyzed using ultraperformance convergence chromatography tandem mass spectrometry and liquid chromatography tandem mass spectrometry. Their short-term and long-term stabilities were investigated by measuring quality control samples at low and high concentrations against freshly prepared calibration standards. Measured concentrations at each time point were compared with the concentrations at T = 0. Antibiotics were considered stable if recovery results were between 85% and 115%. RESULTS: Short-term stability results indicated ceftriaxone, cefuroxime, and meropenem to be stable up to 24 hours at room temperature. All evaluated antibiotics, except imipenem, were stable on ice in a cool box for 24 hours. Amoxicillin, benzylpenicillin, and piperacillin were stable for 24 hours at 4-6°C. Cefotaxime, ceftazidime, cefuroxime, and meropenem were stable at 4-6°C up to 72 hours. Ceftriaxone and flucloxacillin were stable for 1 week at 4-6°C. Long-term stability results showed that all antibiotics were stable up to 1 year at -80°C, except imipenem and piperacillin, which were stable for 6 months at -80°C. CONCLUSIONS: Plasma samples for amoxicillin, benzylpenicillin, cefotaxime, ceftazidime, flucloxacillin, and piperacillin may be stored for a maximum of 24 hours in a cool box. Refrigeration is suitable for plasma samples of amoxicillin, benzylpenicillin, meropenem, and piperacillin for up to 24 hours and cefotaxime, ceftriaxone, ceftazidime and cefuroxime for 72 hours. Plasma samples for imipenem should be frozen directly at -80°C. For long-term storage, plasma samples can be stored at -80°C for a maximum of 6 months for imipenem and piperacillin and 12 months for all other evaluated antibiotics.</p

Which patients benefit from model-informed precision dosing of beta-lactam antibiotics and ciprofloxacin at the ICU?

Objectives: Antibiotic dosing is not optimal in the ICU. Our recent trial investigated the effect of model-informed precision dosing (MIPD) of beta-lactam antibiotics and ciprofloxacin and showed no significant differences in clinical outcomes in all patients. This study aimed to identify subgroups of patients in which the MIPD of these antibiotics could be beneficial for clinical outcomes. Methods: We analysed data from the DOLPHIN randomized controlled trial, which compared MIPD to standard dosing of beta-lactam antibiotics and ciprofloxacin in 388 ICU patients. We divided patients into subgroups based on baseline characteristics and assessed the effect of MIPD on 28-day mortality, 6-month mortality, change in sequential organ failure assessment (delta-SOFA), and ICU length of stay (LOS). Results: We found a lower 28-day mortality in patients with a SOFA below 8 randomized to MIPD (OR 0.40; 95% CI 0.17–0.88). However, patients with a higher SOFA show an increased 28-day mortality (OR 1.94; 95% CI 1.07–3.59) in the MIPD group. ICU LOS was increased in patients receiving MIPD with a SOFA below 8 (IRR 1.36; 95% CI 1.01–1.83) and those receiving MIPD for ceftriaxone (IRR 1.76; 95% CI 1.24–2.51). Patients receiving a dose recommendation within 24 hours show a trend towards decreased ICU LOS (IRR 0.77; 95% CI 0.52–1.16) and higher delta-SOFA (estimate -1.19; 95% CI -2.98–0.60). Conclusions: ICU patients with a SOFA below 8 using MIPD had an increased ICU LOS but a lower 28-day mortality. Fast dose recommendations using MIPD of beta-lactam antibiotics and ciprofloxacin needs to be investigated in ICU patients.</p

Predicting Beta-Lactam Target Non-Attainment in ICU Patients at Treatment Initiation:Development and External Validation of Three Novel (Machine Learning) Models

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.</p

A narrative review of predictors for β-lactam antibiotic exposure during empirical treatment in critically ill patients

Introduction: : Emerging studies suggest that antibiotic pharmacokinetics (PK) are difficult to predict in critically ill patients. The high intra- and inter-patient PK variability makes it challenging to accurately predict the appropriate dosage required for a given patient. Identifying patients at risk could help clinicians to consider more individualized dosing regimens and perform therapeutic drug monitoring. We provide an overview of relevant predictors associated with target (non-)attainment of β-lactam antibiotics in critically ill patients. Areas covered: : This narrative review summarizes patient and clinical characteristics that can help to predict the attainment of target serum concentrations and to provide guidance on antimicrobial dose optimization. Literature was searched using Embase and Medline database, focusing on β-lactam antibiotics in critically ill patients. Expert opinion: : Adequate concentration attainment can be anticipated in critically ill patients prior to initiating empiric β-lactam antibiotic therapy based on readily available demographic and clinical factors. Male gender, younger age, and augmented renal clearance were the most significant predictors for target non-attainment and should be considered in further investigations to develop dosing algorithms for optimal β-lactam therapy

Barriers and Facilitators in the Clinical Implementation of Beta-Lactam Therapeutic Drug Monitoring in Critically Ill Patients: A Critical Review

BACKGROUND: With increasing knowledge of beta-lactam pharmacodynamics and interpatient and intrapatient variability in pharmacokinetics, the usefulness of therapeutic drug monitoring (TDM) is becoming increasingly clear. However, little research has been conducted to identify potential barriers and facilitators in the clinical implementation of beta-lactam TDM. This study provides an overview of the current practices of beta-lactam TDM and barriers and facilitators in its implementation. METHODS: A systematic search was conducted using the Ovid MEDLINE database in April 2021, without restrictions on the publication date. All studies reporting the implementation of beta-lactam antibiotic TDM in critically ill patients through questionnaires or surveys were included in this review. RESULTS: Six eligible studies were identified from 215 records, all of which were cross-sectional. All studies identified barriers and facilitators in the implementation of beta-lactam TDM in critically ill patients. The main barriers were insufficient knowledge about various aspects regarding the implementation of beta-lactam TDM and the unavailability of assays. Furthermore, a delay in the acquisition of TDM results reduces the probability of physicians altering drug dosages. Finally, doubts about the cost-effectiveness and clinical effectiveness of beta-lactam TDM in critically ill patients hinder broad implementation. Moreover, to improve the willingness of physicians to use beta-lactam TDM, collaboration between physicians and clinical pharmacists and clinical microbiologists should be strengthened. CONCLUSIONS: Although the evidence for application of beta-lactam TDM continues to grow, its clinical implementation remains limited. To enable optimal implementation of these antibiotics in critically ill patients, several barriers need to be overcome regarding logistics, equipment availability, clinical evidence, and proof of cost-effectiveness

High-throughput analysis for the simultaneous quantification of nine beta-lactam antibiotics in human plasma by UPC2-MS/MS: Method development, validation, and clinical application

Quantification of beta-lactam antibiotics can be performed by using liquid chromatography in combination with tandem mass spectrometry (MS/MS) or ultraviolet (UV) detection. Since beta-lactam antibiotics are known as highly polar analytes, using standard reversed phase chromatography will result in very early elution, which is often not desirable. Some retention is preferred to reduce matrix effects, because a high amount of non-retained molecular matrix species elute early from the column. For highly polar analytes, ultra-performance convergence chromatography (UPC2) may be a suitable alternative. This method is based on supercritical fluid chromatography. To our knowledge, we developed the first UPC2-MS/MS method for the determination of amoxicillin, benzylpenicillin, flucloxacillin, piperacillin, cefotaxime, cefuroxime, ceftazidime, imipenem, meropenem, and the free fraction of cefuroxime and flucloxacillin in human plasma. The method was validated according to the Food and Drug Administration guidelines. The method was found linear (r2 >0.990) for all analytes. The inaccuracies and imprecisions were < 15% for all analytes. The matrix effect and recovery were nearly all consistent with coefficient of variation of less than 15% and no significant carryover effect was observed. Furthermore, this method was found to be suitable for daily routine analysis in hospital settings, requiring only 50 µL of plasma

Therapeutic Drug Monitoring of Antibiotics in Critically Ill Patients: Current Practice and Future Perspectives With a Focus on Clinical Outcome

PURPOSE: Early initiation of antibiotics is essential for ameliorating infections in critically ill patients. The correct dosage of antibiotics is imperative to ensure their adequate exposure. Critically ill patients have altered pharmacokinetic parameters and are often infected by less susceptible microorganisms. Differences in drug disposition are not considered with standard doses of antibiotics. This can lead to suboptimal antibiotic exposure in critically ill patients. To overcome this problem of suboptimal dosing, therapeutic drug monitoring (TDM) is a strategy commonly used to support individualized dosing of antibiotics. It is routinely used for vancomycin and aminoglycosides in clinical practice. In recent years, it has become apparent that TDM may also be used in other antibiotics. METHODS: This review summarizes the evidence for TDM of antibiotics in critically ill patients, focuses on clinical outcomes, and summarizes possibilities for optimized TDM in the future. RESULTS AND CONCLUSION: After reviewing the literature, we can conclude that general TDM implementation is advised for glycopeptides and aminoglycosides, as evidence of the relationship between TDM and clinical outcome is present. For antibiotics, such as beta-lactams, fluoroquinolones, and linezolid, it seems rational to perform TDM in specific patient cases. TDM involving other antibiotics is supported by individual cases, specifically to decrease toxicity. When focusing on future possibilities to improve TDM of antibiotics in critically ill patients, implementation of model-informed precision dosing should be investigated because it can potentially streamline the TDM process. The logistics of TDM, such as turnaround time and available equipment, are challenging but may be overcome by rapid bioanalytical techniques or real-time monitoring of drug concentrations through biosensors in the future. Education, clinical information on targets, and clinical outcome studies are other important factors that facilitate TDM implementation

Health Care Costs of Target Attainment for Beta-Lactam Antibiotics in Critically Ill Patients: A Retrospective Analysis of the EXPAT Study

BACKGROUND: Optimizing beta-lactam antibiotic treatment is a promising method to reduce the length of intensive care unit (ICU) stay and therefore reduce ICU costs. We used data from the EXPAT trial to determine whether beta-lactam antibiotic target attainment is a cost determinant in the ICU. METHODS: Patients included in the EXPAT trial were divided into target attainment and target nonattainment based on serum antibiotic levels. All hospital costs were extracted from the hospital administration system and categorized. RESULTS: In total, 79 patients were included in the analysis. Target attainment showed a trend toward higher total ICU costs (€44,600 versus €28,200, P = 0.103). This trend disappeared when correcting for ICU length of stay (€2680 versus €2700). Renal replacement therapy was the most important cost driver. CONCLUSIONS: Target attainment for beta-lactam antibiotics shows a trend toward higher total costs in ICU patients, which can be attributed to the high costs of a long stay in the ICU and renal replacement therapy

Predicting Beta-Lactam Target Non-Attainment in ICU Patients at Treatment Initiation:Development and External Validation of Three Novel (Machine Learning) Models

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.</p