Scheetz, Marc H.

ABSTRACT Beta‐lactam antibiotics (beta‐lactams) are first‐line treatments for most major infectious syndromes in acutely ill patients, with in vitro activity against common pathogens, demonstrated efficacy in trials, and a perceived low risk of adverse effects. The current dosing approach, informed by population‐level data, tends to be simplistically reduced to a “one size fits all” dosing method which only accounts for body weight (i.e., in pediatrics) and end organ function to estimate drug clearance (e.g., estimated glomerular filtration rate); this approach results in substantial variability in observed serum concentrations in acutely ill patients, which can compromise real‐world effectiveness and safety. Beta‐lactam dose individualization, therefore, defined as a dosing regimen for one patient informed by measured concentrations from that patient, has been recommended in international clinical guidelines. Comprehensive guidance on best practices for beta‐lactam dose individualization is lacking. To address this knowledge gap and develop guidance, a multidisciplinary panel of international experts was assembled from the disciplines of infectious diseases, critical care, pharmacometrics, and laboratory medicine, representing both adults and pediatrics. The panel systematically evaluated the literature, using the GRADE approach where feasible, to address broad thematic questions pertaining to whether beta‐lactam dose individualization should be pursued, for what indications beta‐lactam dose individualization is warranted, and the most critical considerations and best practices for implementation of beta‐lactam individualization. The resultant consensus recommendations will equip healthcare professionals caring for acutely ill patients treated with beta‐lactam therapy with the evidence and tools necessary to guide optimal use of beta‐lactam dose individualization.

Accurate assessment of renal function is fundamental to dosing renally eliminated drugs. For decades, serum creatinine–based estimating equations have been used to approximate glomerular filtration rate (GFR) for this purpose. While these equations perform reasonably well at the population level, they exhibit substantial individual‐level imprecision and inaccuracy. Simultaneously, recent efforts to remove race from estimating equations addressed important ethical concerns but did not resolve the core limitation of population‐based estimation for individual drug dosing. In this perspective, we argue that personalized dosing requires a shift away from demographic surrogates toward direct measurement of renal clearance and clarify when incremental therapeutic complexity is warranted. We review the limitations of endogenous biomarkers, discuss the role of cystatin C, and propose exogenously measured GFR using iohexol integrated within a Bayesian pharmacometric framework as a clinically actionable approach to individualized drug dosing. Practically, this framework can be implemented by administering a small iohexol dose, collecting sparse timed samples, estimating absolute mGFR and its uncertainty with Bayesian software, and using that posterior estimate to refine renal dose selection.

OBJECTIVES: Estimated glomerular filtration rate is more accurate with combined creatinine and cystatin C equations (eGFRcr-cys) than creatinine alone. This study created and evaluated a cefepime dosing nomogram based on eGFRcr-cys for initial dosing in the critically ill. DESIGN: Pharmacokinetic modeling and simulation study. SETTING: Academic medical center. PATIENTS: Critically ill adults treated with cefepime. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data from 120 patients with baseline cystatin C and follow-up cefepime levels were used to develop a nomogram based on eGFRcr-cys and weight for initial cefepime dosing. The predicted proportion of patients who achieved a free cefepime concentration above the minimum inhibitory concentration of the organism for 100% of the dosing interval in the first 24 hours (100% ƒT > MIC at 24 hr) was compared between administered doses and those predicted by the nomogram doses. Overall drug exposure was estimated with the free area under the concentration time curve from 0 to 24 hours (ƒAUC0–24) and compared between administered and nomogram doses. Achievement of 100% ƒT > MIC at 24 hours was predicted to be significantly better with the nomogram compared with the administered dose (76% vs. 38%; p < 0.001). The median ƒAUC0–24 as predicted by the nomogram (666 mg·hr/L) was slightly higher than the actual ƒAUC0–24 with administered doses (612 mg·hr/L; p = 0.01), but the nomogram led to fewer ƒAUC0–24 values which were either too high (> 900) or too low (< 300) (7% vs. 20%; p = 0.004). CONCLUSIONS: Use of a cystatin C-inclusive dosing nomogram for cefepime could improve target attainment without increasing the risk of potentially toxic levels in the critically ill.

IMPORTANCE: Meropenem dosing is typically guided by creatinine-based estimated glomerular filtration rate (eGFR), but creatinine is a suboptimal GFR marker in the critically ill. OBJECTIVES: This study aimed to develop and qualify a population pharmacokinetic model for meropenem in critically ill adults and to determine which eGFR equation based on creatinine, cystatin C, or both biomarkers best improves model performance. DESIGN, SETTING, AND PARTICIPANTS: This single-center study evaluated adults hospitalized in an ICU who received IV meropenem from 2018 to 2022. Patients were excluded if they had acute kidney injury, were on kidney replacement therapy, or were treated with extracorporeal membrane oxygenation. Two cohorts were used for population pharmacokinetic modeling: a richly sampled development cohort (n = 19) and an opportunistically sampled qualification cohort (n = 32). MAIN OUTCOMES AND MEASURES: A nonlinear mixed-effects model was developed using parametric methods to estimate meropenem serum concentrations. RESULTS: The best-fit structural model in the richly sampled development cohort was a two-compartment model with first-order elimination. The final model included time-dependent weight normalized to a 70-kg adult as a covariate for volume of distribution (Vd) and time-dependent eGFR for clearance. Among the eGFR equations evaluated, eGFR based on creatinine and cystatin C expressed in mL/min best-predicted meropenem clearance. The mean (se) Vd in the final model was 18.2 (3.5) liters and clearance was 11.5 (1.3) L/hr. Using the development cohort as the Bayesian prior, the opportunistically sampled cohort demonstrated good accuracy and low bias. CONCLUSIONS AND RELEVANCE: Contemporary eGFR equations that use both creatinine and cystatin C improved meropenem population pharmacokinetic model performance compared with creatinine-only or cystatin C-only eGFR equations in adult critically ill patients.

ABSTRACT Cefepime exhibits highly variable pharmacokinetics in critically ill patients. The purpose of this study was to develop and qualify a population pharmacokinetic model for use in the critically ill and investigate the impact of various estimated glomerular filtration rate (eGFR) equations using creatinine, cystatin C, or both on model parameters. This was a prospective study of critically ill adults hospitalized at an academic medical center treated with intravenous cefepime. Individuals with acute kidney injury or on kidney replacement therapy or extracorporeal membrane oxygenation were excluded. A nonlinear mixed-effects population pharmacokinetic model was developed using data collected from 2018 to 2022. The 120 included individuals contributed 379 serum samples for analysis. A two-compartment pharmacokinetic model with first-order elimination best described the data. The population mean parameters (standard error) in the final model were 7.84 (0.24) L/h for CL1 and 15.6 (1.45) L for V1. Q was fixed at 7.09 L/h and V2 was fixed at 10.6 L, due to low observed interindividual variation in these parameters. The final model included weight as a covariate for volume of distribution and the eGFR cr-cysC (mL/min) as a predictor of drug clearance. In summary, a population pharmacokinetic model for cefepime was created for critically ill adults. The study demonstrated the importance of cystatin C to prediction of cefepime clearance. Cefepime dosing models which use an eGFR equation inclusive of cystatin C are likely to exhibit improved accuracy and precision compared to dosing models which incorporate an eGFR equation with only creatinine.

Recent clinical studies have reported additive nephrotoxicity with the combination of vancomycin and piperacillin-tazobactam. However, preclinical models have failed to replicate this finding.

Background: Beta-lactam therapeutic drug monitoring (BL TDM; drug level testing) can facilitate improved outcomes in critically ill patients. However, only 10%–20% of hospitals have implemented BL TDM. This study aimed to characterize provider perceptions and key considerations for successfully implementing BL TDM. Methods: This was a sequential mixed-methods study from 2020 to 2021 of diverse stakeholders at 3 academic medical centers with varying degrees of BL TDM implementation (not implemented, partially implemented, and fully implemented). Stakeholders were surveyed, and a proportion of participants completed semistructured interviews. Themes were identified, and findings were contextualized with implementation science frameworks. Results: Most of the 138 survey respondents perceived that BL TDM was relevant to their practice and improved medication effectiveness and safety. Integrated with interview data from 30 individuals, 2 implementation themes were identified: individual internalization and organizational features. Individuals needed to internalize, make sense of, and agree to BL TDM implementation, which was positively influenced by repeated exposure to evidence and expertise. The process of internalization appeared more complex with BL TDM than with other antibiotics (ie, vancomycin). Organizational considerations relevant to BL TDM implementation (eg, infrastructure, personnel) were similar to those identified in other TDM settings. Conclusions: Broad enthusiasm for BL TDM among participants was found. Prior literature suggested that assay availability was the primary barrier to implementation; however, the data revealed many more individual and organizational attributes, which impacted the BL TDM implementation. Internalization should particularly be focused on to improve the adoption of this evidence-based practice.

AbstractStudy ObjectiveIn critically ill patients, adequacy of early antibiotic exposure has been incompletely evaluated. This study characterized factors associated with inadequate cefepime exposure in the first 24 h of critical illness.DesignProspective cohort study.SettingAcademic Medical Center.PatientsCritically ill adults treated with cefepime. Patients with acute kidney injury or treated with kidney replacement therapy or extracorporeal membrane oxygenation were excluded.InterventionNone.MeasurementsA nonlinear mixed‐effects pharmacokinetic (PK) model was developed to estimate cefepime concentrations for each patient over time. The percentage of time the free drug concentration exceeded 8 mg/L during the first 24 h of therapy was calculated (%ƒT>8; appropriate for the susceptible breakpoint for Pseudomonas aeruginosa). Factors predictive of low %ƒT>8 were explored with multivariable regression.Main ResultsIn the 100 included patients, a one‐compartment PK model was developed with first‐order elimination with covariates for weight and estimated glomerular filtration rate based on creatinine and cystatin C (eGFRSCr‐CysC). The median (interquartile range) %ƒT>8 for cefepime in the first 24 h of therapy based on this model was 85% (66%, 100%). Less than 100% ƒT>8 during first 24 h of therapy occurred in 70 (70%) individuals. Lower Sequential Organ Failure Assessment score (p = 0.032) and higher eGFRSCr‐CysC (p < 0.001) predicted a lower %ƒT>8. Central nervous system infection source was protective (i.e., associated with a higher %ƒT>8; p = 0.008).ConclusionsDuring early critical illness, cefepime concentrations were inadequate in a significant proportion of patients. Antimicrobial optimization is needed to improve the precision of pharmacotherapy in the critically ill patients.