What Are the Current Approaches to Optimising Antimicrobial Dosing in the Intensive Care Unit?

Achievement of therapeutic antibiotic exposures using Bayesian dosing software in critically unwell children and adults with sepsis

PURPOSE

Early recognition and effective treatment of sepsis improves outcomes in critically ill patients. However, antibiotic exposures are frequently suboptimal in the intensive care unit (ICU) setting. We describe the feasibility of the Bayesian dosing software Individually Designed Optimum Dosing Strategies (ID-ODS™), to reduce time to effective antibiotic exposure in children and adults with sepsis in ICU.

METHODS

A multi-centre prospective, non-randomised interventional trial in three adult ICUs and one paediatric ICU. In a pre-intervention Phase 1, we measured the time to target antibiotic exposure in participants. In Phase 2, antibiotic dosing recommendations were made using ID-ODS™, and time to target antibiotic concentrations were compared to patients in Phase 1 (a pre-post-design).

RESULTS

175 antibiotic courses (Phase 1 = 123, Phase 2 = 52) were analysed from 156 participants. Across all patients, there was no difference in the time to achieve target exposures (8.7 h vs 14.3 h in Phase 1 and Phase 2, respectively, p = 0.45). Sixty-one courses in 54 participants failed to achieve target exposures within 24 h of antibiotic commencement (n = 36 in Phase 1, n = 18 in Phase 2). In these participants, ID-ODS™ was associated with a reduction in time to target antibiotic exposure (96 vs 36.4 h in Phase 1 and Phase 2, respectively, p < 0.01). These patients were less likely to exhibit subtherapeutic antibiotic exposures at 96 h (hazard ratio (HR) 0.02, 95% confidence interval (CI) 0.01-0.05, p < 0.01). There was no difference observed in in-hospital mortality.

CONCLUSIONS

Dosing software may reduce the time to achieve target antibiotic exposures. It should be evaluated further in trials to establish its impact on clinical outcomes.

Factors Influencing Integration and Usability of Model-Informed Precision Dosing Software in the Intensive Care Unit

BACKGROUND

 Antimicrobial dosing in critically ill patients is challenging and model-informed precision dosing (MIPD) software may be used to optimize dosing in these patients. However, few intensive care units (ICU) currently adopt MIPD software use.

OBJECTIVES

 To determine the usability of MIPD software perceived by ICU clinicians and identify implementation barriers and enablers of software in the ICU.

METHODS

 Clinicians (pharmacists and medical staff) who participated in a wider multicenter study using MIPD software were invited to participate in this mixed-method study. Participants scored the industry validated Post-study System Usability Questionnaire (PSSUQ, assessing software usability) and Technology Acceptance Model 2 (TAM2, assessing factors impacting software acceptance) survey. Semistructured interviews were used to explore survey responses. The framework approach was used to identify factors influencing software usability and integration into the ICU from the survey and interview data.

RESULTS

 Seven of the eight eligible clinicians agreed to participate in the study. The PSSUQ usability scores ranked poorer than the reference norms (2.95 vs. 2.62). The TAM2 survey favorably ranked acceptance in all domains, except image. Qualitatively, key enablers to workflow integration included clear and accessible data entry, visual representation of recommendations, involvement of specialist clinicians, and local governance of software use. Barriers included rigid data entry systems and nonconformity of recommendations to local practices.

CONCLUSION

 Participants scored the MIPD software below the threshold that implies good usability. Factors such as availability of software support by specialist clinicians was important to participants while rigid data entry was found to be a deterrent.

Practical Lessons on Antimicrobial Therapy for Critically Ill Patients

Sepsis stands as a formidable global health challenge, with persistently elevated mortality rates in recent decades. Each year, sepsis not only contributes to heightened morbidity but also imposes substantial healthcare costs on survivors. This narrative review aims to highlight the targeted measures that can be instituted to alleviate the incidence and impact of sepsis in intensive care. Here we discuss measures to reduce nosocomial infections and the prevention of equipment and patient colonisation by resilient pathogens. The overarching global crisis of bacterial resistance to newly developed antimicrobial agents intensifies the imperative for antimicrobial stewardship and de-escalation. This urgency has been accentuated in recent years, notably during the COVID-19 pandemic, as high-dose steroids and opportunistic infections presented escalating challenges. Ongoing research into airway colonisation's role in influencing disease outcomes among critically ill patients underscores the importance of tailoring treatments to disease endotypes within heterogeneous populations, which are important lessons for intensivists in training. Looking ahead, the significance of novel antimicrobial delivery systems and drug monitoring is poised to increase. This narrative review delves into the multifaceted barriers and facilitators inherent in effectively treating critically ill patients vulnerable to nosocomial infections. The future trajectory of intensive care medicine hinges on the meticulous implementation of vigilant stewardship programs, robust infection control measures, and the continued exploration of innovative and efficient technological solutions within this demanding healthcare landscape.

Efficiency of dosing software using Bayesian forecasting in achieving target antibiotic exposures in critically ill patients, a prospective cohort study

INTRODUCTION

Broad-spectrum antibiotics such as beta-lactams and vancomycin are frequently used to treat critically ill patients, however, a significant number do not achieve target exposures. Therapeutic drug monitoring (TDM) combined with Bayesian forecasting dosing software may improve target attainment in these patients. This study aims to describe the efficiency of dosing software for achieving target exposures of selected beta-lactam antibiotics and vancomycin in critically ill patients.

METHODS

A prospective cohort study was undertaken in an adult intensive care unit (ICU). Patients prescribed vancomycin, piperacillin-tazobactam and meropenem were included if they exhibited a subtherapeutic or supratherapeutic exposure informed by TDM. The dosing software, ID-ODS™, was used to generate dosing recommendations which could be either accepted or rejected by the treating team. Repeat antibiotic TDM were requested to determine if target exposures were achieved.

RESULTS

Between March 2020 and December 2021, 70 were included in the analysis. Software recommendations were accepted for 56 patients (80%) with 50 having repeated antibiotic measurements. Forty-three of the 50 patients (86%) achieved target exposures after one software recommendation, with 3 of the remaining 7 patients achieving target exposures after 2. Forty-seven patients out of the 50 patients (94%) achieved the secondary outcome of clinical cure. There were no antibiotic exposure-related adverse events reported.

CONCLUSION

The use of TDM combined with Bayesian forecasting dosing software increases the efficiency for achieving target antibiotic exposures in the ICU. Clinical trials comparing this approach with other dosing strategies are required to further validate these findings.

In silico evaluation of a beta-lactam dosing guideline among adults with serious infections

STUDY OBJECTIVE

The aim of this study was to compare the achievement of therapeutic pharmacokinetic-pharmacodynamic (PK-PD) exposure targets for beta-lactam antibiotics using product information dosing or guideline-based dosing for the treatment of serious infections.

DESIGN

In silico study.

DATA SOURCE

ID-ODSTM (Individually Designed Optimum Dosing Strategies).

PATIENTS AND INTERVENTION

None.

MEASUREMENTS AND MAIN RESULTS

In silico product information and guideline-based dosing simulations for cefepime, ceftazidime, flucloxacillin, meropenem, and piperacillin/tazobactam were performed using pharmacokinetic models from seriously ill patient populations. The median simulated concentration at 48 and 96 h was used to measure the probability of target attainment (PTA) to achieve predefined therapeutic and toxicity PK-PD targets. A multiple linear regression model was constructed to identify the effect of guideline-based dosing covariates on achieving pre-defined therapeutic targets. In total, 480 dosing simulations were performed. The PTA percentage with guideline-based dosing at 48 and 96 h was 80% and 68%, respectively, yielding significantly higher results when compared to product information dosing (48.45% and 49%, respectively), p < 0.001 at both time points. At 48 h, predefined toxicity thresholds were exceeded in 4.7% and 0% of simulations for guideline-based and product information-based dosing, respectively (p = 0.002). eGFR was significantly associated with the % PTA by guideline-based dosing, with eGFR values of 20 and 50 ml/min both statistically significant in leading to an increase in PTA.

CONCLUSIONS

Our study demonstrated that achievement of PK-PD exposures associated with an increased likelihood of effectiveness was more likely to occur with guideline-based dosing; especially at 48 h.

The clinical application of beta-lactam antibiotic therapeutic drug monitoring in the critical care setting

Critically ill patients have increased variability in beta-lactam antibiotic (beta-lactam) exposure due to alterations in their volume of distribution and elimination. Therapeutic drug monitoring (TDM) of beta-lactams, as a dose optimization and individualization tool, has been recommended to overcome this variability in exposure. Despite its potential benefit, only a few centres worldwide perform beta-lactam TDM. An important reason for the low uptake is that the evidence for clinical benefits of beta-lactam TDM is not well established. TDM also requires the availability of specific infrastructure, knowledge and expertise. Observational studies and systematic reviews have demonstrated that TDM leads to an improvement in achieving target concentrations, a reduction in potentially toxic concentrations and improvement of clinical and microbiological outcomes. However, a small number of randomized controlled trials have not shown a mortality benefit. Opportunities for improved study design are apparent, as existing studies are limited by their inclusion of heterogeneous patient populations, including patients that may not even have infection, small sample size, variability in the types of beta-lactams included, infections caused by highly susceptible bacteria, and varied sampling, analytical and dosing algorithm methods. Here we review the fundamentals of beta-lactam TDM in critically ill patients, the existing clinical evidence and the practical aspects involved in beta-lactam TDM implementation.

In silico Evaluation of a Vancomycin Dosing Guideline Among Adults with Serious Infections

BACKGROUND

This study aimed to compare the achievement of pharmacokinetic-pharmacodynamic (PK-PD) exposure targets for vancomycin using a newly developed dosing guideline with product-information-based dosing in the treatment of adult patients with serious infections.

METHODS

In silico product-information- and guideline-based dosing simulations for vancomycin were performed across a range of doses and patient characteristics, including body weight, age, and renal function at 36-48 and 96 hours, using a pharmacokinetic model derived from a seriously ill patient population. The median simulated concentration and area under the 24-hour concentration-time curve (AUC 0-24 ) were used to measure predefined therapeutic, subtherapeutic, and toxicity PK-PD targets.

RESULTS

Ninety-six dosing simulations were performed. The pooled median trough concentration target with guideline-based dosing at 36 and 96 hours was achieved in 27.1% (13/48) and 8.3% (7/48) of simulations, respectively. The pooled median AUC 0-24 /minimum inhibitory concentration ratio with guideline-based dosing at 48 and 96 hours was attained in 39.6% (19/48) and 27.1% (13/48) of simulations, respectively. Guideline-based dosing simulations yielded improved trough target attainment compared with product-information-based dosing at 36 hours and significantly less subtherapeutic drug exposure. The toxicity threshold was exceeded in 52.1% (25/48) and 0% (0/48) for guideline- and product-information-information-based dosing, respectively ( P < 0.001).

CONCLUSIONS

A Critical care vancomycin dosing guideline appeared slightly more effective than standard dosing, as per product information, in achieving PK-PD exposure associated with an increased likelihood of effectiveness. In addition, this guideline significantly reduced the risk of subtherapeutic exposure. The risk of exceeding toxicity thresholds, however, was greater with the guideline, and further investigation is suggested to improve dosing accuracy and sensitivity.

Therapeutic drug monitoring of carbapenem antibiotics in critically ill patients: an overview of principles, recommended dosing regimens, and clinical outcomes

INTRODUCTION

The importance of antibiotic treatment for sepsis in critically ill septic patients is well established. Consistently achieving the dose of antibiotics required to optimally kill bacteria, minimize the development of resistance, and avoid toxicity is challenging. The increasing understanding of the pharmacokinetic and pharmacodynamic (PK/PD) characteristics of antibiotics, and the effects of critical illness on key PK/PD parameters, is gradually re-shaping how antibiotics are dosed in critically ill patients.

AREAS COVERED

The PK/PD characteristics of commonly used carbapenem antibiotics, the principles of the application of therapeutic drug monitoring (TDM), and current as well as future methods of utilizing TDM to optimally devise dosing regimens will be reviewed. The limitations and evidence-base supporting the use of carbapenem TDM to improve outcomes in critically ill patients will be examined.

EXPERT OPINION

It is important to understand the principles of TDM in order to correctly inform dosing regimens. Although the concept of TDM is attractive, and the ability to utilize PK software to optimize dosing in the near future is expected to rapidly increase clinicians' ability to meet pre-defined PK/PD targets more accurately, current evidence provides only limited support for the use of TDM to guide carbapenem dosing in critically ill patients.

Optimization of Therapy and the Risk of Probiotic Use during Antibiotherapy in Septic Critically Ill Patients: A Narrative Review

Optimizing the entire therapeutic regimen in septic critically ill patients should be based not only on improving antibiotic use but also on optimizing the entire therapeutic regimen by considering possible drug–drug or drug–nutrient interactions. The aim of this narrative review is to provide a comprehensive overview on recent advances to optimize the therapeutic regimen in septic critically ill patients based on a pharmacokinetics and pharmacodynamic approach. Studies on recent advances on TDM-guided drug therapy optimization based on PK and/or PD results were included. Studies on patients <18 years old or with classical TDM-guided therapy were excluded. New approaches in TDM-guided therapy in septic critically ill patients based on PK and/or PD parameters are presented for cefiderocol, carbapenems, combinations beta-lactams/beta-lactamase inhibitors (piperacillin/tazobactam, ceftolozane/tazobactam, ceftazidime/avibactam), plazomicin, oxazolidinones and polymyxins. Increased midazolam toxicity in combination with fluconazole, nephrotoxic synergism between furosemide and aminoglycosides, life-threatening hypoglycemia after fluoroquinolone and insulin, prolonged muscle weakness and/or paralysis after neuromuscular blocking agents and high-dose corticosteroids combinations are of interest in critically ill patients. In the real-world practice, the use of probiotics with antibiotics is common; even data about the risk and benefits of probiotics are currently spares and inconclusive. According to current legislation, probiotic use does not require safety monitoring, but there are reports of endocarditis, meningitis, peritonitis, or pneumonia associated with probiotics in critically ill patients. In addition, probiotics are associated with risk of the spread of antimicrobial resistance. The TDM-guided method ensures a true optimization of antibiotic therapy, and particular efforts should be applied globally. In addition, multidrug and drug–nutrient interactions in critically ill patients may increase the likelihood of adverse events and risk of death; therefore, the PK and PD particularities of the critically ill patient require a multidisciplinary approach in which knowledge of clinical pharmacology is essential.

Accuracy of a precision dosing software program for predicting antibiotic concentrations in critically ill patients

BACKGROUND

Critically ill patients with sepsis are predisposed to physiological changes that can reduce the probability of achieving target antibiotic exposures. Precision dosing software programs may be used to improve probability of obtaining these target exposures.

OBJECTIVE

To quantify the accuracy of a precision dosing software program for predicting antibiotic concentrations as well as to assess the impact of using software predictions on actual dosing adjustments.

PATIENTS AND METHODS

The software program ID-ODS was used to predict concentrations for piperacillin, meropenem and vancomycin using patient covariate data with and without the use of therapeutic drug monitoring (TDM) data. The impact of these predictions on actual dosage adjustments was determined by using software predicted concentrations versus measured concentrations.

RESULTS

Software predictions for piperacillin and meropenem exhibited large bias that improved with the addition of TDM data (bias improved from -28.8 to -2.0 mg/L for piperacillin and -3.0 to -0.1 mg/L for meropenem). Dosing changes using predicted concentrations of piperacillin and meropenem with TDM data versus measured concentrations were matched on 89.2% (107/120) and 71% (9/69) occasions, respectively. Although vancomycin predictions demonstrated good accuracy with and without TDM, these findings were limited by our small sample size.

CONCLUSION

These data demonstrate that precision dosing software programs may have scope to reasonably predict antibiotic concentrations in critically ill patients with sepsis. The addition of TDM data improves the predictive performance of the software for all three antibiotics and the ability to anticipate the correct dose change required.

Development of a Predictive Dosing Nomogram to Achieve PK/PD Targets of Amikacin Initial Dose in Critically Ill Patients: A Non-Parametric Approach

French guidelines recommend reaching an amikacin concentration of ≥8 × MIC 1 h after beginning infusion (C_1h), with MIC = 8 mg/L for probabilistic therapy. We aimed to elaborate a nomogram guiding clinicians in choosing the right first amikacin dose for ICU patients in septic shock. A total of 138 patients with 407 observations were prospectively recruited. A population pharmacokinetic model was built using a non-parametric, non-linear mixed-effects approach. The total body weight (TBW) influenced the central compartment volume, and the glomerular filtration rate (according to the CKD-EPI formula) influenced its clearance. A dosing nomogram was produced using Monte Carlo simulations of the amikacin amount needed to achieve a C_1h ≥ 8 × MIC. The dosing nomogram recommended amikacin doses from 1700 mg to 4200 mg and from 28 mg/kg to 49 mg/kg depending on the patient's TBW and renal clearance. However, a C_through ≤ 2.5 mg/L 24 h and 48 h after an optimal dose of amikacin was obtained with probabilities of 0.20 and 0.81, respectively. Doses ≥ 30 mg/kg are required to achieve a C_1h ≥ 8 × MIC with MIC = 8 mg/L. Targeting a MIC = 8 mg/L should depend on local ecology.

Nosocomial Extracardiac Infections After Cardiac Surgery

Purpose of Review

Nosocomial extracardiac infections after cardiac surgery are a major public health issue affecting 3–8.2% of patients within 30–60 days following the intervention.

Recent Findings

Here, we have considered the most important postoperative infective complications that, in order of frequency, are pneumonia, surgical site infection, urinary tract infection, and bloodstream infection. The overall picture that emerges shows that they cause a greater perioperative morbidity and mortality with a longer hospitalization time and excess costs. Preventive interventions and corrective measures, diminishing the burden of nosocomial extracardiac infections, may reduce the global costs. A multidisciplinary team may assure a more appropriate management of nosocomial extracardiac infections leading to a reduction of hospitalization time and mortality rate.

Summary

The main and most current data on epidemiology, prevention, microbiology, diagnosis, and management for each one of the most important postoperative infective complications are reported. The establishment of an antimicrobial stewardship in each hospital seems to be, at the moment, the more valid strategy to counteract the challenging problems.

Assessment of current practice for β-lactam therapeutic drug monitoring in French ICUs in 2021: a nationwide cross-sectional survey

BACKGROUND

Current guidelines and literature support the use of therapeutic drug monitoring (TDM) to optimize β-lactam treatment in adult ICU patients.

OBJECTIVES

To describe the current practice of β-lactam monitoring in French ICUs.

METHODS

A nationwide cross-sectional survey was conducted from February 2021 to July 2021 utilizing an online questionnaire that was sent as an email link to ICU specialists (one questionnaire per ICU).

RESULTS

Overall, 119 of 221 (53.8%) French ICUs participated. Eighty-seven (75%) respondents reported having access to β-lactam TDM, including 52 (59.8%) with on-site access. β-Lactam concentrations were available in 24-48 h and after 48 h for 36 (41.4%) and 26 (29.9%) respondents, respectively. Most respondents (n = 61; 70.1%) reported not knowing whether the β-lactam concentrations in the TDM results were expressed as unbound fractions or total concentrations. The 100% unbound fraction of the β-lactam above the MIC was the most frequent pharmacokinetic and pharmacodynamic target used (n = 62; 73.0%).

CONCLUSIONS

Despite the publication of international guidelines, β-lactam TDM is not optimally used in French ICUs. The two major barriers are β-lactam TDM interpretation and the required time for results.

Antimicrobial safety considerations in critically ill patients: part I: focused on acute kidney injury

INTRODUCTION

Antibiotic prescription is a challenging issue in critical care settings. Different pharmacokinetic and pharmacodynamic properties, polypharmacy, drug interactions, and high incidence of multidrug-resistant microorganisms in this population can influence the selection, safety, and efficacy of prescribed antibiotics.

AREAS COVERED

In the current article, we searched PubMed, Scopus, and Google Scholar for estimating renal function in acute kidney injury, nephrotoxicity of commonly used antibiotics, and nephrotoxin stewardship in intensive care units.

EXPERT OPINION

Early estimation of kidney function with an accurate method may be helpful to optimize antimicrobial treatment in critically ill patients. Different antibiotic dosing regimens may be required for patients with acute kidney injury. In many low-resource settings, therapeutic drug monitoring is not available for antibiotics. Acute kidney injury may influence treatment effectiveness and patient outcome.

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

In the era of “Bad Bugs, No Drugs,” optimizing antibiotic therapy against multi-drug resistant (MDR) pathogens is crucial. Mathematical modelling has been employed to further optimize dosing regimens. These models include mechanism-based PK/PD models, systems-based models, quantitative systems pharmacology (QSP) and population PK models. Quantitative systems pharmacology has significant potential in precision antimicrobial chemotherapy in the clinic. Population PK models have been employed in model-informed precision dosing (MIPD). Several antibiotics require close monitoring and dose adjustments in order to ensure optimal outcomes in patients with infectious diseases. Success or failure of antibiotic therapy is dependent on the patient, antibiotic and bacterium. For some drugs, treatment responses vary greatly between individuals due to genotype and disease characteristics. Thus, for these drugs, tailored dosing is required for successful therapy. With antibiotics, inappropriate dosing such as insufficient dosing may put patients at risk of therapeutic failure which could lead to mortality. Conversely, doses that are too high could lead to toxicities. Hence, precision dosing which customizes doses to individual patients is crucial for antibiotics especially those with a narrow therapeutic index. In this review, we discuss the various strategies in optimizing antimicrobial therapy to address the challenges in the management of infectious diseases and delivering personalized therapy.

Therapeutic Drug Monitoring of Antifungal Agents in Critically Ill Patients: Is There a Need for Dose Optimisation?

Invasive fungal infections are an important cause of morbidity and mortality, especially in critically ill patients. Increasing resistance rates and inadequate antifungal exposure have been documented in these patients, due to clinically relevant pharmacokinetic (PK) and pharmacodynamic (PD) alterations, leading to treatment failure. Physiological changes such as third spacing (movement of fluid from the intravascular compartment to the interstitial space), hypoalbuminemia, renal failure and hepatic failure, as well as common interventions in the intensive care unit, such as renal replacement therapy and extracorporeal membrane oxygenation, can lead to these PK and PD alterations. Consequently, a therapeutic target concentration that may be useful for one patient may not be appropriate for another. Regular doses do not take into account the important PK variations in the critically ill, and the need to select an effective dose while minimising toxicity advocates for the use of therapeutic drug monitoring (TDM). This review aims to describe the current evidence regarding optimal PK/PD indices associated with the clinical efficacy of the most commonly used antifungal agents in critically ill patients (azoles, echinocandins, lipid complexes of amphotericin B, and flucytosine), provide a comprehensive understanding of the factors affecting the PK of each agent, document the PK parameters of critically ill patients compared to healthy volunteers, and, finally, make recommendations for therapeutic drug monitoring (TDM) of antifungals in critically ill patients.

Treatment of ventilator-associated pneumonia due to carbapenem-resistant Gram-negative bacteria with novel agents: a contemporary, multidisciplinary ESGCIP perspective

INTRODUCTION

: In the past 15 years, treatment of VAP caused by carbapenem-resistant Gram-negative bacteria (CR-GNB) has represented an intricate challenge for clinicians.

AREAS COVERED

In this perspective article, we discuss the available clinical data about novel agents for the treatment of CR-GNB VAP, together with general PK/PD principles for the treatment of VAP, in the attempt to provide some suggestions for optimizing antimicrobial therapy of CR-GNB VAP in the daily clinical practice.

EXPERT OPINION

Recently, novel BL and BL/BLI combinations have become available that have shown potent in vitro activity against CR-GNB and have attracted much interest as novel, less toxic, and possibly more efficacious options for the treatment of CR-GNB VAP compared with previous standard of care. Besides randomized controlled trials, a good solution to enrich our knowledge on how to use these novel agents at best in the near future, while at the same time remaining adherent to current evidence-based guidelines, is to improve our collaboration to conduct larger multinational observational studies to collect sufficiently large populations treated in real life with those novel agents for which guidelines currently do not provide a recommendation (in favor or against) for certain causative organisms.

Artificial Intelligence in Infection Management in the ICU

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2022. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2022. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901.

Pooled Population Pharmacokinetic Analysis for Exploring Ciprofloxacin Pharmacokinetic Variability in Intensive Care Patients

Background and Objective

Previous pharmacokinetic (PK) studies of ciprofloxacin in intensive care (ICU) patients have shown large differences in estimated PK parameters, suggesting that further investigation is needed for this population. Hence, we performed a pooled population PK analysis of ciprofloxacin after intravenous administration using individual patient data from three studies. Additionally, we studied the PK differences between these studies through a post-hoc analysis.

Methods

Individual patient data from three studies (study 1, 2, and 3) were pooled. The pooled data set consisted of 1094 ciprofloxacin concentration–time data points from 140 ICU patients. Nonlinear mixed-effects modeling was used to develop a population PK model. Covariates were selected following a stepwise covariate modeling procedure. To analyze PK differences between the three original studies, random samples were drawn from the posterior distribution of individual PK parameters. These samples were used for a simulation study comparing PK exposure and the percentage of target attainment between patients of these studies.

Results

A two-compartment model with first-order elimination best described the data. Inter-individual variability was added to the clearance, central volume, and peripheral volume. Inter-occasion variability was added to clearance only. Body weight was added to all parameters allometrically. Estimated glomerular filtration rate on ciprofloxacin clearance was identified as the only covariate relationship resulting in a drop in inter-individual variability of clearance from 58.7 to 47.2%. In the post-hoc analysis, clearance showed the highest deviation between the three studies with a coefficient of variation of 14.3% for posterior mean and 24.1% for posterior inter-individual variability. The simulation study showed that following the same dose regimen of 400 mg three times daily, the area under the concentration–time curve of study 3 was the highest with a mean area under the concentration–time curve at 24 h of 58 mg·h/L compared with that of 47.7 mg·h/L for study 1 and 47.6 mg·h/L for study 2. Similar differences were also observed in the percentage of target attainment, defined as the ratio of area under the concentration–time curve at 24 h and the minimum inhibitory concentration. At the epidemiological cut-off minimum inhibitory concentration of Pseudomonas aeruginosa of 0.5 mg/L, percentage of target attainment was only 21%, 18%, and 38% for study 1, 2, and 3, respectively.

Conclusions

We developed a population PK model of ciprofloxacin in ICU patients using pooled data of individual patients from three studies. A simple ciprofloxacin dose recommendation for the entire ICU population remains challenging owing to the PK differences within ICU patients, hence dose individualization may be needed for the optimization of ciprofloxacin treatment.

Biomarkers Predicting Tissue Pharmacokinetics of Antimicrobials in Sepsis: A Review

The pathophysiology of sepsis alters drug pharmacokinetics, resulting in inadequate drug exposure and target-site concentration. Suboptimal exposure leads to treatment failure and the development of antimicrobial resistance. Therefore, we seek to optimize antimicrobial therapy in sepsis by selecting the right drug and the correct dosage. A prerequisite for achieving this goal is characterization and understanding of the mechanisms of pharmacokinetic alterations. However, most infections take place not in blood but in different body compartments. Since tissue pharmacokinetic assessment is not feasible in daily practice, we need to tailor antibiotic treatment according to the specific patient’s pathophysiological processes. The complex pathophysiology of sepsis and the ineffectiveness of current targeted therapies suggest that treatments guided by biomarkers predicting target-site concentration could provide a new therapeutic strategy. Inflammation, endothelial and coagulation activation markers, and blood flow parameters might be indicators of impaired tissue distribution. Moreover, hepatic and renal dysfunction biomarkers can predict not only drug metabolism and clearance but also drug distribution. Identification of the right biomarkers can direct drug dosing and provide timely feedback on its effectiveness. Therefore, this might decrease antibiotic resistance and the mortality of critically ill patients. This article fills the literature gap by characterizing patient biomarkers that might be used to predict unbound plasma-to-tissue drug distribution in critically ill patients. Although all biomarkers must be clinically evaluated with the ultimate goal of combining them in a clinically feasible scoring system, we support the concept that the appropriate biomarkers could be used to direct targeted antibiotic dosing.

Pharmacokinetics of meropenem in critically ill patients in Saudi Arabia

Background

Meropenem is commonly used in the ICU to treat gram-negative infections. Due to various pathophysiological changes, critically ill patients are at higher risk of having subtherapeutic concentrations and hence have a higher risk of treatment failure—especially in regions where gram-negative drug resistance is increasing, such as Saudi Arabia. No studies have evaluated the pharmacokinetics of meropenem in critically ill patients in Saudi Arabia. Our primary objective is to assess the percentage of patients achieving the therapeutic target for meropenem.

Methods

This prospective observational study was conducted in the ICUs of King Khalid University Hospital. Patient were included if >18 years-of-age and received meropenem for a clinically suspected or proven bacterial infection. The primary outcome was to assess the percentage of patients who achieved the pharmacokinetic/pharmacodynamic (PKPD) therapeutic target of a free trough concentration four times the MIC. The secondary outcome was to estimate the pharmacokinetics of meropenem. Pharmacokinetic analysis was performed using Monolix Suite 2020R1 (Lixoft, France).

Results

Trough concentrations were highly variable and ranged from <0.5 µg/mL to 39 µg/mL, with a mean ± SD trough concentration of 8.5 ± 8 µg/mL. Only 46% of patients achieved the therapeutic target. The only significant predictor of failing to achieve the PKPD target was augmented renal clearance.

Conclusion

In conclusion, more than half of our patients did not achieve the PKPD target. Thus, there is a need for better dosing strategies of meropenem in critically ill patients in Saudi Arabia such as extended and continuous infusion.

Efficacy and appropriateness of novel antibiotics in response to antimicrobial-resistant Gram-negative bacteria in patients with sepsis in the ICU

INTRODUCTION

There is an ever-increasing range of antibiotic-resistant pathogens that have led to higher community-acquired infections, and substantial mortality rates in critically ill patients.

AREAS COVERED

We have critically appraised available evidence through a structured literature review, investigating effective empiric antibiotic administration and appropriateness on outcomes of critically ill patients with an increased risk of developing resistant pathogens. The use of new antibiotics should be determined based on relevant knowledge of their spectrum and properties to provide effective mode of action for critically ill patients.

EXPERT OPINION

Restricting severely ill patients access to new broad-spectrum empirical drugs is not the answer. Rather there should be a focus on identifying host response to infection to differentiate between colonization or contamination and true infection, and the sensitivity to antibiotics used in the intensive care unit (ICU).

Management relies on adequate antibiotic administration, the ability to monitor response, and facilitate the cessation of antibiotic treatment. The major determinant of patient success in a patient with a severe infection is the 'right' antibiotic or complementary course of treatment. As an overarching criterion, the following 3 appropriate "Ds" should be considered: Dosing, Duration and De-escalation to empirically assess the right antibiotic optimal antimicrobial selection.

Pharmacokinetics of Antibiotics in Pediatric Intensive Care: Fostering Variability to Attain Precision Medicine

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.

Emerging therapeutic drug monitoring of anti-infective agents in Australian hospitals: Availability, performance and barriers to implementation

AIMS

The purpose of the study was to assess the status of emerging therapeutic drug monitoring (TDM) of anti-infective agents in Australian hospitals.

METHODS

A nationwide cross-sectional survey of all Australian hospitals operating in the public and private health sector was conducted between August and September 2019. The survey consisted of questions regarding institutional TDM practice for anti-infective agents and clinical vignettes specific to β-lactam antibiotics.

RESULTS

Responses were received from 82 unique institutions, representing all Australian states and territories. All 29 (100%) of principal referral (major) hospitals in Australia participated. Five surveys were partially complete. Only 25% (20/80) of hospitals had TDM testing available on-site for any of the eight emerging TDM candidates considered: β-lactam antibiotics, anti-tuberculous agents, flucytosine, fluoroquinolones, ganciclovir, human immunodeficiency virus (HIV) drugs, linezolid and teicoplanin. A considerable time lag was noted between TDM sampling and reporting of results. With respect to β-lactam antibiotic TDM, variable indications, pharmacodynamic targets and sampling times were identified. The three greatest barriers to local TDM performance were found to be (1) lack of timely assays/results, (2) lack of institutional-wide expertise and/or training and (3) lack of guidelines to inform ordering of TDM and interpretation of results. The majority of respondents favoured establishing national TDM guidelines and increasing access to dose prediction software, at rates of 89% and 96%, respectively.

CONCLUSION

Translating emerging TDM evidence into daily clinical practice is slow. Concerted efforts are required to address the barriers identified and facilitate the implementation of standardised practice.

Artificial Intelligence for Clinical Decision Support in Sepsis

Sepsis is one of the main causes of death in critically ill patients. Despite the continuous development of medical technology in recent years, its morbidity and mortality are still high. This is mainly related to the delay in starting treatment and non-adherence of clinical guidelines. Artificial intelligence (AI) is an evolving field in medicine, which has been used to develop a variety of innovative Clinical Decision Support Systems. It has shown great potential in predicting the clinical condition of patients and assisting in clinical decision-making. AI-derived algorithms can be applied to multiple stages of sepsis, such as early prediction, prognosis assessment, mortality prediction, and optimal management. This review describes the latest literature on AI for clinical decision support in sepsis, and outlines the application of AI in the prediction, diagnosis, subphenotyping, prognosis assessment, and clinical management of sepsis. In addition, we discussed the challenges of implementing and accepting this non-traditional methodology for clinical purposes.

The Minimum Inhibitory Concentration of Antibiotics: Methods, Interpretation, Clinical Relevance

Inefficiency of medical therapies used in order to cure patients with bacterial infections requires not only to actively look for new therapeutic strategies but also to carefully select antibiotics based on variety of parameters, including microbiological. Minimal inhibitory concentration (MIC) defines in vitro levels of susceptibility or resistance of specific bacterial strains to applied antibiotic. Reliable assessment of MIC has a significant impact on the choice of a therapeutic strategy, which affects efficiency of an infection therapy. In order to obtain credible MIC, many elements must be considered, such as proper method choice, adherence to labeling rules, and competent interpretation of the results. In this paper, two methods have been discussed: dilution and gradient used for MIC estimation. Factors which affect MIC results along with the interpretation guidelines have been described. Furthermore, opportunities to utilize MIC in clinical practice, with pharmacokinetic /pharmacodynamic parameters taken into consideration, have been investigated. Due to problems related to PK determination in individual patients, statistical estimation of the possibility of achievement of the PK/PD index, based on the Monte Carlo, was discussed. In order to provide comprehensive insights, the possible limitations of MIC, which scientists are aware of, have been outlined.

[Pharmacokinetic modifications and pharmacokinetic/pharmacodynamic optimization of beta-lactams in ICU]

Pharmacokinetic modifications in critically ill patients and those induced by ICU therapeutics raise a lot of issues about antibiotic dose adaptation. Beta-lactams are anti-infectious widely used in ICU. Frequent beta-lactam underdoses induce a risk of therapeutic failure potentially lethal and of emergence of bacterial resistance. Overdoses expose to a neurotoxic and nephrotoxic risk. Therefore, an understanding of pharmacokinetics modifications appears to be essential. A global pharmacokinetic/pharmacodynamic approach is required, including use of prolonged or continued beta-lactam infusions to optimise probability of pharmacokinetic/pharmacodynamic target attainment. Beta-lactam therapeutic drug monitoring should also be considered. Experts agree to target a free plasma betalactam concentration above four times the MIC of the causative bacteria for 100 % of the dosing interval. Bayesian methods could permit individualized doses adaptations.