population based pharmacokinetic modelling with Bayesian estimation in paediatric ICU
Augmented renal clearance (ARC) is a phenomenon in critically ill patients characterized by increased creatinine clearance and elimination of renally eliminated medications. What was previously reported as a condition prevalent in adult populations, recent studies have shown its increasing prevalence as well in pediatric intensive care population. Patients with ARC under antibiotic administration are at risk of subtherapeutic antibiotic exposure and therefore need higher dosages to avoid life-threatening complications. In order to identify ARC, estimated glomerular filtration (eGFR) is the gold standard measurement for the assessment of renal function but method to obtain this value has been challenging and unreliable. Aminoglycoside drug clearance is an alternative measure to obtain eGFR because it is freely filtered with minimum non-renal clearance. By identifying ARC in paediatric patients, it will allow us to adjust dosage regimens with optimal pharmacokinetic profile.
Indeed, optimizing dosing strategies in critically ill patients with ARC remains a goal of continued research. In a recent publication in the Journal of Antimicrobial Chemotherapy, scientists at University of California San Diego: Professor John Bradley, Joshua Valdez and Dr. Jennifer Le together with Dr. Sean Avedissian, Dr. Nathaniel Rhodes, and Yuna Kim at Midwestern university conducted a retrospective study to identify the prevalence of ARC from population data in two hospitals. The researchers used PK modelling and Bayesian posterior estimation to calculate aminoglycoside clearance. They selected one and two compartment clearance models as base models and aminoglycoside concentration was calculated from the ultimate best fit model. Additionally, to measure variables contributing as risk factors for ARC, multivariate logistic model was used.
The authors observed that there was a significant prevalence of ARC in the two paediatric populations. Two compartment model was used in the final PK analysis and multiple aminoglycoside concentration was fitted into the model to calculate overall clearance. The overall clearance model required value for creatine clearance, total body weight, serum creatinine and maturation term. They reported a prevalence of ARC of 19.5% in the paediatric patients with a median clearance of 157 ml/min/1.73m2.
Furthermore, the research team identified factors that contributed to the risk of ARC in paediatric population including increasing age, sepsis and low baseline serum creatinine. Additionally, increased clearance was correlated with decreased 24-hour AUC (body exposure to drug over the first 24 hour). This showed that with further studies aminoglycoside can be a reliable alternative to measure eGFR in paediatric population.
This is the first report that used population PK modelling and Bayesian estimation to determine ARC in a paediatric patient population. In a statement to Medicine Innovates, Professor Jennifer Le, the corresponding author, explained that their study showed paediatric patients experiencing ARC require higher doses to reach recommended PK/PD target exposures. ARC is often overlooked in this population due to unreliable screening methods and subsequently affects the optimal therapeutic dosage range. The study indeed will pave the way in understanding the importance of ARC in paediatric population and henceforth taking necessary actions to avoid complications. Recently, increasing antibiotic resistance is detrimental to the healthcare system especially in an ICU setting hospital. Using methods similar to the ones in the study as the basis for ARC detection along with further research will give insight into a suitable dosing regimen for ARC patients and therefore decrease the chances of antibiotic resistance in them. It will help us advance our understanding in possible pathophysiological mechanism for ARC and ultimately strategize in the management of ARC patients.
Avedissian S., Rhodes N., Kim Y., Bradley J., Valdez J., Le J., Augmented renal clearance of aminoglycosides using population-based pharmacokinetic modelling with Bayesian estimation in paediatric ICU, Journal of Antimicrobial Chemotherapy,2020;75: 162-169Go To Journal of Antimicrobial Chemotherapy