1015: POPULATION PHARMACOKINETIC EVALUATION OF VANCOMYCIN IN CRITICALLY ILL CHILDREN WITH SEPSIS

ObjectivesTo study the effect of organ failure and inflammation on midazolam clearance in critically ill children, using population pharmacokinetic modeling.MethodsA total of 83 critically ill children (median age 5 months (range 1 day-17 years), n=523 samples) receiving intravenous midazolam for continuous sedation during mechanical ventilation were included. Disease severity was described using the validated and clinically used scores PELOD, PIM2 and PRISM II. Cytokines (IL-1, IL-2, IL-6, TNF-a) and C-reactive protein (CRP) were used as markers for inflammation. A population pharmacokinetic model for midazolam was developed using NONMEM 7.3. Body weight, age, severity of organ failure and inflammatory markers were considered as potential covariates.ResultsIn a two-compartmental PK model, body weight was found as most significant covariate for clearance and volume of distribution. Moreover, both severity of organ failure (PELOD) and inflammation (IL6 and CRP) were significant determinants of clearance (p<0.01), and either of these factors improved the model significantly. With increasing number of organ failures, midazolam clearance significantly reduced. CRP was linearly correlated with clearance (slope −0.095), with higher CRP levels resulting in lower clearances. Either one of the covariates could explain part of the variability in clearance.ConclusionFor midazolam clearance, apart from body weight, we found organ failure reflected by the PELOD score, and inflammation reflected by IL6 and CRP, as significant covariates. Most likely this effect is due to reduced activity of CYP3A in critically ill mechanically ventilated children. Both CRP concentration and organ failure should be considered when dosing midazolam and potentially other CYP3A substrates in critically ill children.

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Population Pharmacokinetics and Pharmacodynamics of Extended-Infusion Piperacillin and Tazobactam in Critically Ill Children

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.02089-15 ◽

2015 ◽

Vol 60 (1) ◽

pp. 522-531 ◽

Cited By ~ 18

Author(s):

Kristen Nichols ◽

Eun Kyoung Chung ◽

Chad A. Knoderer ◽

Lauren E. Buenger ◽

Daniel P. Healy ◽

...

Keyword(s):

Steady State ◽

Population Pharmacokinetics ◽

Critically Ill ◽

Critically Ill Children ◽

Population Pharmacokinetic ◽

Pharmacokinetic Data ◽

Pharmacokinetics And Pharmacodynamics ◽

Study Objective ◽

Population Pharmacokinetics And Pharmacodynamics ◽

Extended Infusion

ABSTRACTThe study objective was to evaluate the population pharmacokinetics and pharmacodynamics of extended-infusion piperacillin-tazobactam in children hospitalized in an intensive care unit. Seventy-two serum samples were collected at steady state from 12 patients who received piperacillin-tazobactam at 100/12.5 mg/kg of body weight every 8 h infused over 4 h. Population pharmacokinetic analyses were performed using NONMEM, and Monte Carlo simulations were performed to estimate the piperacillin pharmacokinetic profiles for dosing regimens of 80 to 100 mg/kg of the piperacillin component given every 6 to 8 h and infused over 0.5, 3, or 4 h. The probability of target attainment (PTA) for a cumulative percentage of the dosing interval that the drug concentration exceeds the MIC under steady-state pharmacokinetic conditions (TMIC) of ≥50% was calculated at MICs ranging from 0.25 to 64 mg/liter. The mean ± standard deviation (SD) age, weight, and estimated glomerular filtration rate were 5 ± 3 years, 17 ± 6.2 kg, and 118 ± 41 ml/min/1.73 m2, respectively. A one-compartment model with zero-order input and first-order elimination best fit the pharmacokinetic data for both drugs. Weight was significantly associated with piperacillin clearance, and weight and sex were significantly associated with tazobactam clearance. Pharmacokinetic parameters (mean ± SD) for piperacillin and tazobactam were as follows: clearance, 0.22 ± 0.07 and 0.19 ± 0.07 liter/h/kg, respectively; volume of distribution, 0.43 ± 0.16 and 0.37 ± 0.14 liter/kg, respectively. All extended-infusion regimens achieved PTAs of >90% at MICs of ≤16 mg/liter. Only the 3-h infusion regimens given every 6 h achieved PTAs of >90% at an MIC of 32 mg/liter. For susceptible bacterial pathogens, piperacillin-tazobactam doses of ≥80/10 mg/kg given every 8 h and infused over 4 h achieve adequate pharmacodynamic exposures in critically ill children.

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Maturation of midazolam clearance in critically ill children with severe bronchiolitis: A population pharmacokinetic analysis

European Journal of Pharmaceutical Sciences ◽

10.1016/j.ejps.2019.105095 ◽

2020 ◽

Vol 141 ◽

pp. 105095 ◽

Cited By ~ 1

Author(s):

Mojca Kerec Kos ◽

Mirjana Miksić ◽

Marija Jovanović ◽

Robert Roškar ◽

Štefan Grosek ◽

...

Keyword(s):

Critically Ill ◽

Population Pharmacokinetic Analysis ◽

Critically Ill Children ◽

Pharmacokinetic Analysis ◽

Population Pharmacokinetic

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O33 Towards personalised weaning of sedatives and analgesics using mechanism-based modelling of iatrogenic withdrawal in critically ill children

Archives of Disease in Childhood ◽

10.1136/archdischild-2019-esdppp.33 ◽

2019 ◽

Vol 104 (6) ◽

pp. e14.3-e15

Author(s):

S Goulooze ◽

E Krekels ◽

M van Dijk ◽

T Hankemeier ◽

D Tibboel ◽

...

Keyword(s):

Critically Ill ◽

Rating Scale ◽

Numerical Rating Scale ◽

Statistical Significance ◽

Prolonged Treatment ◽

Morphine Dependence ◽

Critically Ill Children ◽

Population Pharmacokinetic ◽

List Type ◽

Over Time

BackgroundProlonged treatment with analgesics and sedatives can result in iatrogenic withdrawal syndrome (IWS) in children being weaned from these drugs.1Personalized weaning strategies might lower the incidence of IWS, but this requires a quantitative understanding of withdrawal over time in individual patients.MethodsData from 81 children (aged 1 month to 17 years) collected during an observational clinical study on IWS2 were used, including a total of 1782 withdrawal assessments performed by PICU nurses, on a numerical rating scale (NRSwithdrawal) from 0 (no withdrawal) to 10 (worst withdrawal possible). Population pharmacokinetic models from literature were used to generate concentration-time profiles in each patient of all key analgesics and sedatives: morphine, fentanyl, methadone, midazolam, lorazepam, propofol, esketamine and clonidine. A mechanism-based withdrawal model was developed using NONMEM 7.3 to quantify IWS over time. The final model was used to perform simulations in which different weaning strategies were compared.ResultsA novel mechanism-based withdrawal model structure was developed with a hypothetical compartment, which equilibrates with the central pharmacokinetic compartment, and which characterizes the development and disappearance of drug dependence over time. With this model and available data, withdrawal dynamics could be established with statistical significance for fentanyl (p< 10-6), morphine (p=0.043) and esketamine (p=0.002), and not for any of the other drugs. Compared with fentanyl, development and disappearance of esketamine and morphine dependence is slower.ConclusionsGiven the patient‘s use of fentanyl, morphine and esketamine, the developed model can dynamically predict IWS from these substances under different weaning strategies. The results show that the optimal strategy for weaning of drug dependent children depends on both the type of drug and the drug levels prior to weaning. In this study, there was insufficient information to characterise midazolam withdrawal dynamics, potentially because of slow midazolam weaning with insufficiently high NRSwithdrawal scores.ReferencesBest KM, Boullata JI, Curley MAQ. Risk factors associated with iatrogenic opioid and benzodiazepine withdrawal in critically ill pediatric patients: A Systematic Review and Conceptual Model. Pediatr Crit Care Med ( 2015) 16(2): 175–183.Ista E, de Hoog M, Tibboel D, Duivenvoorden HJ, van Dijk M. Psychometric evaluation of the sophia observation withdrawal symptoms scale in critically ill children. Pediatr Crit Care Med ( 2013).14(8): 761–769.Disclosure(s)Nothing to disclose

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Use of Electronic Health Records to Identify Exposure-Response Relationships in Critically Ill Children: An Example of Midazolam and Delirium

Journal of Pediatric Intensive Care ◽

10.1055/s-0041-1725148 ◽

2021 ◽

Author(s):

Kanecia O. Zimmerman ◽

Tracy G. Spears ◽

Marjan Cobbaert ◽

Felix Boakye-Agyeman ◽

Huali Wu ◽

...

Keyword(s):

Confidence Interval ◽

Electronic Health Records ◽

Critically Ill ◽

Drug Exposure ◽

Critically Ill Children ◽

Population Pharmacokinetic ◽

Parameter Estimates ◽

Health Records ◽

Exposure Response ◽

Electronic Health

AbstractAdverse drug events are common in critically ill children and often result from systemic or target organ drug exposure. Methods of drug dosing and titration that consider pharmacokinetic alterations may improve our ability to optimally dose critically ill patients and reduce the risk for drug-related adverse events. To demonstrate this possibility, we explored the exposure-response relationship between midazolam and delirium in critically ill children. We retrospectively examined electronic health records (EHRs) of critically ill children <18 years of age hospitalized in the pediatric intensive care unit at Duke University; these children were administered midazolam during mechanical ventilation and had ≥1 Cornell Assessment of Pediatric Delirium (CAPD) score. We used individual-level data extracted from the EHR and a previously published population pharmacokinetic (PK) model developed in critically ill children to simulate plasma concentrations at the time of CAPD scores in 1,000 representative datasets. We used multilevel repeated measures models, with clustering at patient and simulation levels, to evaluate the associations between measures of drug exposure (e.g., concentration and area under concentration time curve) and delirium scores. We included 61 children, median age 1.5 years (range = 0.1–16.3), with 181 CAPD assessments. We identified similarities between simulated Empirical Bayesian parameter estimates from the EHR cohort and those from the PK model population. We identified a stronger association between drug concentration at the time of score and CAPD scores (coefficient 1.78; 95% confidence interval: 1.66–1.90) compared with cumulative dose per kilogram and CAPD scores (coefficient −0.01; 95% confidence interval: −0.01 to −0.01). EHR and PK models can be leveraged to investigate exposure-response relationships in critically ill children.

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