Optimization of Vancomycin Initial Dosing Regimen in Neonates Using an Externally Evaluated Population Pharmacokinetic Model.

BACKGROUND: Vancomycin therapeutic monitoring guidelines were revised in March 2020, and a population pharmacokinetics-guided Bayesian approach to estimate the 24-hour area under the concentration-time curve to the minimum inhibitory concentration ratio has since been recommended instead of trough concentrations. To comply with these latest guidelines, we evaluated published population pharmacokinetic models of vancomycin using an external dataset of neonatal patients and selected the most predictive model to develop a new initial dosing regimen. METHODS: The models were identified from the literature and tested using a retrospective dataset of Canadian neonates. Their predictive performance was assessed using prediction- and simulation-based diagnostics. Monte Carlo simulations were performed to develop the initial dosing regimen with the highest probability of therapeutic target attainment. RESULTS: A total of 144 vancomycin concentrations were derived from 63 neonates in the external population. Five of the 28 models retained for evaluation were found predictive with a bias of 15% and an imprecision of 30%. Overall, the Grimsley and Thomson model performed best, with a bias of -0.8% and an imprecision of 20.9%; therefore, it was applied in the simulations. A novel initial dosing regimen of 15 mg/kg, followed by 11 mg/kg every 8 hours should favor therapeutic target attainment. CONCLUSIONS: A predictive population pharmacokinetic model of vancomycin was identified after an external evaluation and used to recommend a novel initial dosing regimen. The implementation of these model-based tools may guide physicians in selecting the most appropriate initial vancomycin dose, leading to improved clinical outcomes.

Does Sample Size, Sampling Strategy, or Handling of Concentrations Below the Lower Limit of Quantification Matter When Externally Evaluating Population Pharmacokinetic Models?

BACKGROUND AND OBJECTIVES: Precision dosing requires selecting the appropriate population pharmacokinetic model, which can be assessed through external evaluations (EEs). The lack of understanding of how different study design factors influence EE study outcomes makes it challenging to select the most suitable model for clinical use. This study aimed to evaluate the impact of sample size, sampling strategy, and handling of concentrations below the lower limit of quantification (BLQ) on the outcomes of EE for four population pharmacokinetic models using vancomycin and tobramycin as examples. METHODS: Three virtual patient populations undergoing vancomycin or tobramycin therapy were simulated with varying sample size and sampling scenarios. The three approaches used to handle BLQ data were to (1) discard them, (2) impute them as LLOQ/2, or (3) use a likelihood-based approach. EEs were performed with NONMEM and R. RESULTS: Sample size did not have an important impact on the EE results for a given scenario. Increasing the number of samples per patient did not improve predictive performance for two out of the three evaluated models. Evaluating a model developed with rich sampling did not result in better performance than those developed with regular therapeutic drug monitoring. A likelihood-based method to handle BLQ samples impacted the outcomes of the EE with lower bias for predicted troughs. CONCLUSIONS: This study suggests that a large sample size may not be necessary for an EE study, and models selected based on TDM may be more generalizable. The study highlights the need for guidelines for EE of population pharmacokinetic models for clinical use.

Vancomycin: An analysis and evaluation of eight population pharmacokinetic models for clinical application in general adult population.

INTRODUCTION: Based on the recent guidelines for vancomycin therapeutic drug monitoring (TDM), the area under the curve to minimum inhibitory concentration ratio was to be employed combined with the usage of population pharmacokinetic (popPK) model for dosing adaptation. Yet, deploying these models in a clinical setting requires an external evaluation of their performance. OBJECTIVES: This study aimed to evaluate existing vancomycin popPK models from the literature for the use in TDM within the general patient population in a clinical setting. METHODS: The models under external evaluation were chosen based on a review of literature covering vancomycin popPK models developed in general adult populations. Patients' data were collected from Charles-Le Moyne Hospital (CLMH). The external evaluation was performed with NONMEM® (v7.5). Additional analyses such as evaluating the impact of number of samples on external evaluation, Bayesian forecasting, and a priori dosing regimen simulations were performed on the best performing model. RESULTS: Eight popPK models were evaluated with an independent dataset that included 40 patients and 252 samples. The model developed by Goti and colleagues demonstrated superior performance in diagnostic plots and population predictive performance, with bias and inaccuracy values of 0.251% and 22.7%, respectively, and for individual predictive performance, bias and inaccuracy were -4.90% and 12.1%, respectively. When limiting the independent dataset to one or two samples per patient, the Goti model exhibited inadequate predictive performance for inaccuracy, with values exceeding 30%. Moreover, the Goti model is suitable for Bayesian forecasting with at least two samples as prior for the prediction of the next trough concentration. Furthermore, the vancomycin dosing regimen that would maximize therapeutic targets of area under the curve to minimum inhibitory concentration ratio (AUC24/MIC) and trough concentrations (Ctrough) for the Goti model was 20 mg/kg/dose twice daily. CONCLUSION: Considering the superior predictive performance and potential for Bayesian forecasting in the Goti model, future research aims to test its applicability in clinical settings at CLMH, both in a priori and a posteriori scenario.

Nlmixr2 Versus NONMEM: An Evaluation of Maximum A Posteriori Bayesian Estimates Following External Evaluation of Gentamicin and Tobramycin Population Pharmacokinetic Models.

The objective of this project is to compare the results of the same study carried out on NONMEM and nlmixr2. This analysis consists of evaluating previously published population pharmacokinetic models of gentamicin and tobramycin in our population of interest with sparse concentrations. A literature review was performed to determine the gentamicin and tobramycin models in critically ill adult patients. In parallel, gentamicin and tobramycin dosing data, information on the treatment, the patient, and the bacteria were collected retrospectively in 2 Quebec establishments. The external evaluations were previously performed using NONMEM Version 7.5. Model equations were rewritten with R, and external evaluations were performed using nlmixr2. Predictive performance was assessed based on the estimation of bias and imprecision of the prediction error for maximum a posteriori (MAP) Bayesian PK parameter and observed concentrations. Comparison between nlmixr2 and NONMEM was performed on 4 gentamicin and 3 tobramycin population pharmacokinetic models. Compared to NONMEM, for gentamicin and tobramycin clearance and central volume of distribution, nlmixr2 produced individual pharmacokinetic parameters with bias values ranging from -32.5% to 5.67% and imprecision values ranging from 6.33% to 32.5%. Despite these differences, population bias and imprecision for sparse concentrations were low and ranged from 0% to 5.3% and 0.2% to 6.5%, respectively. The external evaluations performed with both software packages resulted in the same interpretation in terms of population predictive performance for all 7 models. Nlmxir2 showed comparable predictive performance with NONMEM with sparse concentrations that are, at most, sampled twice within a single dose administration (peak and trough).

Exposure levels and target attainment of piperacillin/tazobactam in adult patients admitted to the intensive care unit: a prospective observational study.

PURPOSE: The objective of this study was to evaluate the exposure and the pharmacodynamic target attainment of piperacillin/tazobactam (PTZ) in adult critically ill patients. METHODS: We conducted a prospective observational study in the intensive care unit (ICU) of the Hôpital du Sacré-Cœur de Montréal (a Level I trauma centre in Montreal, QC, Canada) between January 2021 and June 2022. We included patients aged 18 yr or older admitted to the ICU who received PTZ by intravenous administration. Demographic and clinical characteristics were collected, and clinical scores were calculated. On study day 1 of antimicrobial therapy, three blood samples were collected at the following timepoints: one hour after PTZ dose administration and at the middle and at the end of the dosing interval. The sampling schedule was repeated on days 4 and 7 of therapy if possible. Samples were analyzed by ultra-high performance liquid chromatography with diode array detector to determine the total piperacillin concentration. Middle- and end-of-interval concentrations were used for target attainment analyses, and were defined as a concentration above the minimal inhibitory concentration of 16 mg·L-1, corresponding to the breakpoint of Enterobacteriaceae and Pseudomonas aeruginosa. RESULTS: Forty-three patients were recruited and 202 blood samples were analyzed. The most prevalent dose was 3/0.375 g every six hours (n = 50/73 doses administered, 68%) with a 30-min infusion. We observed marked variability over the three sampling timepoints, and the median [interquartile range] piperacillin concentrations at peak, middle of interval, and end of interval were 109.4 [74.0-152.3], 59.3 [21.1-74.4], and 25.3 [6.8-44.6] mg·L-1, respectively. When assessing target attainment, 37% of patients did not reach the efficacy target of a trough concentration of 16 mg·L-1. The majority of patients who were underexposed were patients with normal to augmented renal clearance. CONCLUSION: In this prospective observational study of adult ICU patients receiving intravenous PTZ, a large proportion had subtherapeutic concentrations of piperacillin. This was most notable in patients with normal to augmented renal clearance. More aggressive dosage regimens may be required for this subpopulation to ensure attainment of efficacy targets.

RéSUMé: OBJECTIF: L'objectif de cette étude était d'évaluer l'exposition et l'atteinte des cibles pharmacodynamiques de la pipéracilline/tazobactam (PTZ) chez la patientèle adulte aux soins intensifs. MéTHODES: Nous avons réalisé une étude observationnelle prospective dans l'unité de soins intensifs (USI) de l'Hôpital du Sacré-Cœur de Montréal (un centre de traumatologie de niveau 1 à Montréal, QC, Canada) entre janvier 2021 et juin 2022. Nous avons inclus les patient·es adultes âgé·es de 18 ans ou plus admis·es à l'USI ayant reçu de la PTZ par administration intraveineuse. Les caractéristiques démographiques et cliniques ont été recueillies, et les scores cliniques ont été calculés. Au jour 1 de la thérapie antimicrobienne, trois échantillons sanguins ont été prélevés aux moments suivants : 1 h après l'administration de la dose de PTZ, au milieu et à la fin de l'intervalle d'administration. Le calendrier d'échantillonnage a été répété aux jours 4 et 7 de la thérapie si possible. Les échantillons ont été analysés par chromatographie liquide à ultra-haute performance avec détecteur à diodes pour déterminer la concentration totale de pipéracilline. Les concentrations du milieu et de fin d'intervalle ont été utilisées pour les analyses d'atteinte de cible, définie comme une concentration supérieure à la concentration minimale inhibitrice de 16 mg·L-1, associée aux Enterobacteriaceae et au Pseudomonas aeruginosa. RéSULTATS: Quarante-trois patient·es ont été recruté·es et 202 échantillons sanguins ont été analysés. La dose la plus prévalente était une dose de 3/0,375 g aux 6 h (n = 50/73 doses administrées, 68 %) avec une perfusion sur 30 min. Nous avons observé une variabilité marquée aux trois temps de prélèvement, et les concentrations médianes [intervalle interquartile] de pipéracilline au pic, au milieu et à la fin de l'intervalle étaient respectivement de 109,4 [74,0-152,3], 59,3 [21,1-74,4] et 25,3 [6,8-44,6] mg·L−1. Lors de l'évaluation de l'atteinte de la cible, 37 % des patient·es n'ont pas atteint la cible d'efficacité d'une concentration de 16 mg·L−1 à la fin de l'intervalle posologique. La majorité des patient·es sous-exposé·es étaient des personnes dont la clairance rénale était normale ou augmentée. CONCLUSION: Dans cette étude observationnelle prospective de patient·es adultes aux soins intensifs recevant de la PTZ par voie intraveineuse, une grande proportion de patient·es présentait des concentrations sous-thérapeutiques de pipéracilline. Ceci était plus marqué chez les patient·es ayant une clairance rénale normale ou augmentée. Des schémas posologiques plus agressifs pourraient être nécessaires pour cette sous-population afin de favoriser l'atteinte des cibles d'efficacité.

Potential benefits of therapeutic drug monitoring for beta-lactam antibiotics in augmented renal clearance patients: a case report.

Augmented renal clearance (ARC) is commonly described in critically ill patients, making drug pharmacokinetics even harder to predict in this population. This case report displays the value of therapeutic drug monitoring (TDM) of piperacillin/tazobactam (PTZ) in this population. We identified two patients with ARC and intermittent administration of PTZ who took part in a prospective, descriptive study conducted at Hôpital du Sacré-Cœur de Montréal. Both had plasma samples drawn at peak, middle, and end of their dosing intervals of PTZ. Minimal inhibitory concentrations (MICs) of 4 and 8 mg/L were chosen to evaluate therapeutic target attainment at middle and end of dosing interval. The first patient was a 52-year-old male with a renal clearance rate estimated at 147 mL/min who received 3.375 g PTZ every 6 h. The second patient, a 49-year-old male, had an estimated renal clearance rate of 163 mL/min and received the same regimen. Both patients had piperacillin concentrations above the target MICs at middle of the dosing interval, but they failed to reach a trough concentration above 8 mg/L. The present case report showcases two patients with subtherapeutic PTZ concentrations despite strict following of local administration protocols. This suboptimal administration could not only lead to treatment failure, but also to the selection and growth of resistant pathogens. Implementing TDM would offer the possibility to adjust drug regimens in real-time and prevent situations like these from occurring.

Toward Model-Based Informed Precision Dosing of Vancomycin in Hematologic Cancer Patients: A First Step.

BACKGROUND AND OBJECTIVE: There is no consensus on the optimal vancomycin dose to achieve pharmacokinetic/pharmacodynamic (PK/PD) target in patients with hematologic cancer or in hematopoietic stem cell transplant (HSCT) recipients. A 24-h area under the concentration-time curve (AUC) >400 mg*h/L must be achieved early for successful treatment of severe methicillin-resistant Staphylococcus aureus (MRSA) infections. Current nomograms derived from general population data are not sufficiently accurate to allow AUC-based model-informed precision dosing. The objective of this study was to characterize vancomycin PK in patients with hematologic cancer or in HSCT recipients and to develop a model-informed dosing tool based on PK/PD target requirements. METHODS: Pooled retrospective and prospective vancomycin serum concentrations were analyzed using NONMEM® to evaluate the performance of previously published population PK (popPK) models built from hematologic cancer datasets and to develop a novel Bayesian PK model. Patients' characteristics and clinical data were tested as potential covariates. The popPK model was validated internally and externally. Predictions of vancomycin concentrations for different dosing regimens were made using Monte-Carlo simulations, and a nomogram strategy was proposed according to selected probability of target attainment (PTA). RESULTS: The predictive performance of the published popPK models was found to be suboptimal for our population. A novel popPK model was developed using 240 vancomycin concentrations (60 patients). A two-compartment structural model with an additive error model best described the data. Ideal body weight and estimated glomerular filtration rate (eGFR) [Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)] were selected as covariates for volume of distribution (V) and clearance (CL). Bootstrapping confirmed the stability and precision of the popPK parameters. The volume of distribution was V1 = 46.8 L and V2 = 56.1 L, while CL = 5.63 L/h. External validation using 107 vancomycin concentrations (24 patients) demonstrated the predictivity of the model. A nomogram was developed to reach minimally PTA >50% for 400 < AUC < 600 mg*h/L. CONCLUSION: To our knowledge, this study provides the first model-informed AUC-based strategy in North American hematologic cancer patients with or without HSCT. The resulting nomogram generated provides a simplified approach to improving the accuracy of initial vancomycin dosing in this population.

ß-Lactam Pharmacokinetic/Pharmacodynamic Target Attainment in Intensive Care Unit Patients: A Prospective, Observational, Cohort Study.

BACKGROUND: The aims of this study were to describe pharmacokinetic/pharmacodynamic target attainment in intensive care unit (ICU) patients treated with continuously infused ß-lactam antibiotics, their associated covariates, and the impact of dosage adjustment. METHODS: This prospective, observational, cohort study was performed in three ICUs. Four ß-lactams were continuously infused, and therapeutic drug monitoring (TDM) was performed at days 1, 4, and 7. The primary pharmacokinetic/pharmacodynamic target was an unbound ß-lactam plasma concentration four times above the bacteria's minimal inhibitory concentration during the whole dosing interval. The demographic and clinical covariates associated with target attainment were evaluated. RESULTS: A total of 170 patients were included (426 blood samples). The percentages of empirical ß-lactam underdosing at D1 were 66% for cefepime, 43% for cefotaxime, 47% for ceftazidime, and 14% for meropenem. Indexed creatinine clearance was independently associated with treatment underdose if increased (adjusted odds ratio per unit, 1.01; 95% CI, 1.00 to 1.01; p = 0.014) or overdose if decreased (adjusted odds ratio per unit, 0.95; 95% CI, 0.94 to 0.97; p < 0.001). Pharmacokinetic/pharmacodynamic target attainment was significantly increased after ß-lactam dosage adjustment between day 1 and day 4 vs. no adjustment (53.1% vs. 26.2%; p = 0.018). CONCLUSIONS: This study increases our knowledge on the optimization of ß-lactam therapy in ICU patients. A large inter- and intra-patient variability in plasmatic concentrations was observed, leading to inadequate exposure. A combined indexed creatinine clearance and TDM approach enables adequate dosing for better pharmacokinetic/pharmacodynamic target attainment.

Towards model-informed precision dosing of piperacillin: multicenter systematic external evaluation of pharmacokinetic models in critically ill adults with a focus on Bayesian forecasting.

PURPOSE: Inadequate piperacillin (PIP) exposure in intensive care unit (ICU) patients threatens therapeutic success. Model-informed precision dosing (MIPD) might be promising to individualize dosing; however, the transferability of published models to external populations is uncertain. This study aimed to externally evaluate the available PIP population pharmacokinetic (PopPK) models. METHODS: A multicenter dataset of 561 ICU patients (11 centers/3654 concentrations) was used for the evaluation of 24 identified models. Model performance was investigated for a priori (A) predictions, i.e., considering dosing records and patient characteristics only, and for Bayesian forecasting, i.e., additionally including the first (B1) or first and second (B2) therapeutic drug monitoring (TDM) samples per patient. Median relative prediction error (MPE) [%] and median absolute relative prediction error (MAPE) [%] were calculated to quantify accuracy and precision. RESULTS: The evaluation revealed a large inter-model variability (A: MPE - 135.6-78.3% and MAPE 35.7-135.6%). Integration of TDM data improved all model predictions (B1/B2 relative improvement vs. A: |MPE|median_all_models 45.1/67.5%; MAPEmedian_all_models 29/39%). The model by Kim et al. was identified to be most appropriate for the total dataset (A/B1/B2: MPE - 9.8/- 5.9/- 0.9%; MAPE 37/27.3/23.7%), Udy et al. performed best in patients receiving intermittent infusion, and Klastrup et al. best predicted patients receiving continuous infusion. Additional evaluations stratified by sex and renal replacement therapy revealed further promising models. CONCLUSION: The predictive performance of published PIP models in ICU patients varied considerably, highlighting the relevance of appropriate model selection for MIPD. Our differentiated external evaluation identified specific models suitable for clinical use, especially in combination with TDM.

External Evaluation of Population Pharmacokinetic Models for Precision Dosing: Current State and Knowledge Gaps.

Predicting drug exposures using population pharmacokinetic models through Bayesian forecasting software can improve individual pharmacokinetic/pharmacodynamic target attainment. However, selecting the most adapted model to be used is challenging due to the lack of guidance on how to design and interpret external evaluation studies. The confusion around the choice of statistical metrics and acceptability criteria emphasises the need for further research to fill this methodological gap as there is an urgent need for the development of standards and guidelines for external evaluation studies. Herein we discuss the scientific challenges faced by pharmacometric researchers and opportunities for future research with a focus on antibiotics.

Tobramycin a Priori Dosing Regimens Based on PopPK Model Simulations in Critically Ill Patients: Are They Transferable?

BACKGROUND: In recent years, multiple population pharmacokinetic models have been developed for drugs such as tobramycin that need therapeutic drug monitoring. Some of these models have been used to develop a priori dosing regimens for their respective populations. However, these dosing regimens may not apply to other populations. Therefore, this study aimed to evaluate tobramycin population pharmacokinetic models in critically ill patients and establish an adequate dosing regimen. METHODS: Evaluated models were identified from a literature review of aminoglycoside population pharmacokinetic models in critically ill patients. After retrospective data collection in 2 Quebec hospitals, external evaluation and model re-estimation were performed with NONMEM (v7.5) to assess imprecision and bias values. Dosing regimens were simulated and compared between the best-performing model and its re-estimated counterparts. RESULTS: None of the 3 evaluated models showed acceptable imprecision or bias values in the data sets of the 19 patients. Similar percentages of target attainment were obtained for the original and re-estimated models after the dosing regimen simulations. CONCLUSION: Although the predictive performance evaluation criteria were inadequate, the original and re-estimated models yielded similar results. This raises the question of what a priori bias and imprecision thresholds should be defined as acceptable for the external evaluation of models to be applied in clinical practice. Studies evaluating the impact of these thresholds are needed.

Development and Evaluation of a Height-Based Tobramycin Initial Dosing Nomogram for the Treatment of Adult Cystic Fibrosis Pulmonary Exacerbations.

ABSTRACT: Tobramycin is widely used to treat pulmonary exacerbations of cystic fibrosis. Height has been previously found to be significantly more predictive of tobramycin pharmacokinetics than body weight. This study aimed to develop a height-based initial dosing nomogram and evaluate its performance in peak concentration (Cmax) precision relative to standard and fixed dosing. Monte Carlo simulations were performed to develop a nomogram representing the doses required to reach Cmax targets at different heights. Cmax data observed at 2 clinical centers [McGill University Health Centre (MUHC) and Institut universitaire de cardiologie et pneumologie de Québec (IUCPQ-UL)] were compared with population-predicted Cmax using the doses derived from the nomogram alongside a fixed dose. Height-based dosing resulted in significantly less variable-predicted Cmax values [coefficient of variation (CV) MUHC = 15.7% and IUCPQ-UL = 10.8%] than the Cmax values observed in clinical practice (CV MUHC = 30.0% and CV IUCPQ-UL = 26.9%) and predicted Cmax values obtained from a fixed dose (CV MUHC = 21.2% and CV IUCPQ-UL = 16.3%). An initial dosing nomogram was developed to help reduce pharmacokinetic variability in the observed Cmax. More precise dosing would allow for better clinical outcomes in adult patients with cystic fibrosis.

New Recommendations of a Height-Based Dosing Regimen of Tobramycin for Cystic Fibrosis in Adults: A Population Pharmacokinetic Analysis.

BACKGROUND: Acute pulmonary exacerbations (APEs) in patients with adult cystic fibrosis (CF) are treated with a beta-lactam and an aminoglycoside for activity against Pseudomonas aeruginosa (PA). Emerging drug resistance and changing pharmacokinetic profile in an aging population involve a reevaluation of tobramycin dosing recommendations. The objective of this study was to develop a population pharmacokinetic model and establish optimal dosing recommendations for tobramycin using Monte Carlo simulations. METHODS: This retrospective clinical study and data collection were performed at the CF center of the McGill University Health Center (MUHC), Canada. Model development and simulations were performed using a nonlinear mixed-effect modeling approach (NONMEM, version 7.4.2). The ratios of maximal concentration (C max ) to the minimal inhibitory concentration (MIC) (C max /MIC ≥8 and ≥10) and area under the curve (AUC) to the MIC (AUC/MIC ≥70 and ≥100) were evaluated. RESULTS: Adult patients with CF (n = 51) treated with tobramycin were included in the study. Plasma concentrations of tobramycin were obtained for 699 samples from the MUHC database. The two-compartmental model best described the pharmacokinetics of tobramycin. The association of patient height with the central volume of distribution significantly improved this model. Height, rather than weight, induced the best reduction in objective function. According to simulations, doses between 3.4 mg/cm and 4.4 mg/cm were necessary to achieve C max /MIC values of ≥8 and ≥10, respectively. However, higher doses were required to achieve the AUC/MIC targets. CONCLUSIONS: This study demonstrated that height of the patients seems to be more suitable than their weight for dosing adjustments in adult patients with CF. According to this model, initial doses of tobramycin between 3.4 and 4.4 mg/cm should be recommended for patients with a median height of 164 cm and weight of 55 kg to achieve the target plasma concentrations.

Impact of piperacillin unbound fraction variability on dosing recommendations in critically ill patients.

A common approach to assess the efficacy of piperacillin is to first measure the total concentration and afterwards apply a theoretical unbound fraction of 70% to obtain the unbound concentration. However, hypoalbuminemia is a common phenomenon in critically ill patients, resulting in variations in unbound fraction, therefore we aimed to simulate the impact of piperacillin unbound fraction fluctuations on the predictive performance of a population pharmacokinetic model and on the dosing recommendations of piperacillin. Unbound factors of 70%, 75%, 80% and 85% were applied to total concentrations of piperacillin administered by continuous infusion from an external dataset. A validated model was used for assessment of predictive performance and to estimate patient clearance. Dosing simulations were performed to evaluate target attainment. Variation in unbound fractions caused minimal impact on piperacillin clearance and target attainment but seemed to influence model validity.

VANCOmycin dose adjustments comparing trough levels to the ratio of the area under de curve to the minimum inhibitory concentration method using a BAYESian approach: A feasibility study.

WHAT IS KNOWN AND OBJECTIVE?: The latest published guidelines advocate for the area under the concentration-time curve to minimal inhibitory concentration (AUC0-24h /MIC) estimated with bayesian calculations. This recommended pharmacokinetic monitoring transition is not based on randomized controlled prospective data. METHODS: In this open-label feasibility RCT, patients were assigned to have their vancomycin dosing adjusted based on bayesian-guided AUC0-24h /MIC or trough levels. Primary outcomes were consent rate, number of patients recruited per month, compliance with blood sampling schedule and compliance with bayesian software recommendations. Secondary outcomes focused on target attainment, safety and operational impacts. RESULTS AND DISCUSSION: Forty-five patients underwent randomization (23 bayesian, 22 trough). Consent rate was 37,5% for an average of 9.8 patients recruited per month meeting pre-specified objectives of 30% (p = 0.073) and 10 (p = 0.74) respectively. A 74.8% compliance with blood sampling schedule was below the pre-specified objective of 80% (p = 0.038). There was no statistically significant difference between the 83.7% compliance with bayesian software recommendations and the pre-specified objective of 90% (p = 0.21). Although exploratory, key clinical results were significant increases in the bayesian group for proportion of levels at target (RR 1.32; 95% CI 1.01-1.72; P = 0.038), number of blood samplings for patients (p = 0.036) and pharmacists' time spent on monitoring (p < 0.0001). A tendency towards a reduced incidence of nephrotoxicity in the Bayesian group was observed (RR 0.57; 95% CI 0.16-2.12; p = 0.46). WHAT IS NEW AND CONCLUSIONS?: This trial demonstrates that it would be feasible to conduct a properly sized RCT comparing vancomycin Bayesian-guided AUC0-24h /MIC to trough level monitoring. Although exploratory, this trial also showed a tendency towards reduced incidence of nephrotoxicity and an increased proportion of dosages at therapeutic targets with Bayesian monitoring.

Model Re-Estimation: An Alternative for Poor Predictive Performance during External Evaluations? Example of Gentamicin in Critically Ill Patients.

BACKGROUND: An external evaluation is crucial before clinical applications; however, only a few gentamicin population pharmacokinetic (PopPK) models for critically ill patients included it in the model development. In this study, we aimed to evaluate gentamicin PopPK models developed for critically ill patients. METHODS: The evaluated models were selected following a literature review on aminoglycoside PopPK models for critically ill patients. The data of patients were retrospectively collected from two Quebec hospitals, the external evaluation and model re-estimation were performed with NONMEM® (v7.5) and the population bias and imprecisions were estimated. Dosing regimens were simulated using the best performing model. RESULTS: From the datasets of 39 and 48 patients from the two Quebec hospitals, none of the evaluated models presented acceptable values for bias and imprecision. Following model re-estimations, all models showed an acceptable predictive performance. An a priori dosing nomogram was developed with the best performing re-estimated model and was consistent based on recommended dosing regimens. CONCLUSION: Due to the poor predictive performance during the external evaluations, the latter must be prioritized during model development. Model re-estimation may be an alternative to developing a new model, especially when most known models display similar covariates.

Risk factors associated with augmented renal clearance in a mixed intensive care unit population: a retrospective study.

BACKGROUND: Augmented renal clearance is increasingly recognized in critically ill patients. This condition may lead to suboptimal dosing of renally excreted medications. AIM: Our primary objective was to identify demographic and clinical factors associated with augmented renal clearance in a mixed critically ill population. METHOD: This retrospective single center observational cohort study evaluated patients admitted in a mixed adult intensive care unit for augmented renal clearance, defined as a creatinine clearance of ≥ 130 ml/min/1.73m2, through weekly 24-h urine collection. Variables associated with augmented renal clearance were identified using univariate analysis, then served as covariates in a backward stepwise logistic regression. Goodness-of-fit of the model was assessed and receiver operating characteristic curve was generated. RESULTS: Augmented renal clearance was observed in 25.3% of the study cohort (n = 324). Age below 50 years (adjusted odds ratio 7.32; 95% CI 4.03-13.29, p < 0.001), lower serum creatinine at intensive care admission (adjusted odds ratio 0.97; 95% CI 0.96-0.99, p < 0.001) and trauma admission (adjusted odds ratio 2.26; 95% CI 1.12-4.54, p = 0.022) were identified as independent risk factors. Our model showed acceptable discrimination in predicting augmented renal clearance (Area under receiver operating characteristic curve (0.810; 95% CI 0.756-0.864, p < 0.001)). CONCLUSION: We identified age below 50 years, lower serum creatinine upon intensive care admission and trauma as independent risk factors for augmented renal clearance, consistent with the literature suggesting that patients with low serum creatinine upon admission could have a higher risk of developing augmented renal clearance.

Validation of the Augmented Renal Clearance in Trauma Intensive Care scoring system for augmented renal clearance prediction in a trauma subgroup of a mixed ICU population.

WHAT IS KNOWN AND OBJECTIVE: Augmented renal clearance is prevalent in trauma patients and leads to subtherapeutic levels of renally eliminated medications with potentially unfavourable clinical outcomes. The Augmented Renal Clearance of Trauma in Intensive Care (ARCTIC) score has been developed to predict augmented renal clearance in critically ill trauma patients. Our primary objective was to validate this score among the trauma subgroup of a mixed intensive care patient cohort. METHODS: This single-centre, retrospective, observational cohort study assessed augmented renal clearance using a timed 24-h urine collection performed weekly. ARC was defined as a measured creatinine clearance of ≥130 ml/min/1.73 m2 . ARCTIC score performance was evaluated through a receiver operator characteristic curves and analysis of sensitivities and specificities for the trauma subgroup, the medical/surgical subgroup and the pooled cohort. RESULTS AND DISCUSSION: Augmented renal clearance was observed in 33.9% (n = 58) of trauma patients (n = 171) and 15.7% (n = 24) of medical/surgical patients (n = 153). Examination of different cutoffs for the ARCTIC score in our trauma population confirmed that the optimal cutoff score was ≥6. Comparison between ROC curves for ARCTIC score and for regression model based upon our data in trauma patients indicated validation of the score in this subgroup. Comparison of sensitivities and specificities for ARCTIC score between trauma (93.1% and 41.6%, respectively) and medical/surgical subjects (87.5% and 49.6%, respectively) showed no clinical nor statistical difference, suggesting validation for the medical/surgical subgroup as well. WHAT IS NEW AND CONCLUSION: In our mixed ICU population, the ARCTIC score was validated in the trauma subgroup. We also found that the score performed well in the medical/surgical population. Future studies should assess the performance of the ARCTIC score prospectively.