Tutorial on model selection and validation of model input into precision dosing software for model-informed precision dosing.

There has been rising interest in using model-informed precision dosing to provide personalized medicine to patients at the bedside. This methodology utilizes population pharmacokinetic models, measured drug concentrations from individual patients, pharmacodynamic biomarkers, and Bayesian estimation to estimate pharmacokinetic parameters and predict concentration-time profiles in individual patients. Using these individualized parameter estimates and simulated drug exposure, dosing recommendations can be generated to maximize target attainment to improve beneficial effect and minimize toxicity. However, the accuracy of the output from this evaluation is highly dependent on the population pharmacokinetic model selected. This tutorial provides a comprehensive approach to evaluating, selecting, and validating a model for input and implementation into a model-informed precision dosing program. A step-by-step outline to validate successful implementation into a precision dosing tool is described using the clinical software platforms Edsim++ and MwPharm++ as examples.

Cefepime pharmacokinetics in critically ill children and young adults undergoing continuous kidney replacement therapy.

OBJECTIVES: Cefepime is an antibiotic commonly used to treat sepsis and is cleared by renal excretion. Cefepime dosing requires adjustment in patients with decreased kidney function and in those receiving continuous kidney replacement therapy (CKRT). We aimed to characterize cefepime PK in a diverse cohort of critically ill paediatric patients on CKRT. METHODS: Patients were identified from an ongoing pharmacokinetic/pharmacodynamic (PK/PD) study of beta-lactam antibiotics, and were included if they had received at least two cefepime doses in the ICU and were on CKRT for at least 24 h. PK parameters were estimated using MwPharm++ with Bayesian estimation and a paediatric population PK model. Target attainment was assessed as time of free cefepime concentrations above minimum inhibitory concentration (fT > 1× or 4 × MIC). RESULTS: Seven patients were included in the study (ages 2 to 20 years). CKRT indications included liver failure (n = 1), renal failure (n = 4) and fluid overload (n = 2). Total effluent flow rates ranged from 1833 to 3115 (mean 2603) mL/1.73 m2/h, while clearance was 2.11-3.70 (mean 3.0) L/h/70 kg. Effluent flows were lower, but clearance and fT > MIC were similar to paediatric data published previously. Using Pseudomonas aeruginosa MIC breakpoints, all patients had 100% of dosing interval above MIC, but only one had 100% of dosing interval above 4× MIC. CONCLUSIONS: Since most patients failed to attain stringent targets of 100% fT > 4×  MIC, model-informed precision dosing may benefit such patients.

ß-lactam precision dosing in critically ill children: Current state and knowledge gaps.

There has been emerging interest in implementing therapeutic drug monitoring and model-informed precision dosing of ß-lactam antibiotics in critically ill patients, including children. Despite a position paper endorsed by multiple international societies that support these efforts in critically ill adults, implementation of ß-lactam precision dosing has not been widely adopted. In this review, we highlight what is known about ß-lactam antibiotic pharmacokinetics and pharmacodynamics in critically ill children. We also define the knowledge gaps that present barriers to acceptance and implementation of precision dosing of ß-lactam antibiotics in critically ill children: a lack of consensus on which subpopulations would benefit most from precision dosing and the uncertainty of how precision dosing changes outcomes. We conclude with opportunities for further research to close these knowledge gaps.

Clinician Accuracy in Identifying and Predicting Organ Dysfunction in Critically Ill Children.

OBJECTIVES: To determine clinician accuracy in the identification and prediction of multiple organ dysfunction syndrome. DESIGN: Prospective cohort study. SETTING: University of Michigan's C.S. Mott Children's Hospital PICU. PATIENTS: Patients admitted to the PICU with an anticipated PICU length of stay greater than 48 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: For each patient, the clinical team (attending, fellow, resident/nurse practitioner) was surveyed regarding existing and anticipated organ dysfunction. The primary outcomes were clinicians' accuracy at identifying multiple organ dysfunction syndrome and predicting new or progressive multiple organ dysfunction syndrome, compared to the objective assessment of multiple organ dysfunction syndrome using Proulx criteria. We also measured sensitivity, specificity, negative and positive predictive values, and negative and positive likelihood ratios of clinician assessments. We tested for differences in accuracy by clinician type using chi-square tests. Clinicians rated their confidence in prediction on a 5-point Likert scale. There were 476 eligible PICU admissions, for whom 1,218 surveys were completed. Multiple organ dysfunction syndrome was present in 89 patients (18.7%) at enrollment, and new or progressive multiple organ dysfunction syndrome occurred in 39 (8.2%). Clinicians correctly identified multiple organ dysfunction syndrome with 79.9% accuracy and predicted additional organ dysfunction with 82.6% accuracy. However, the positive and negative likelihood ratios for new or progressive multiple organ dysfunction syndrome prediction were 3.0 and 0.7, respectively, indicating a weak relationship between the clinician prediction and development of new or progressive multiple organ dysfunction syndrome. The positive predictive value of new or progressive multiple organ dysfunction syndrome prediction was just 22.1%. We found no differences in accuracy by clinician type for either identification of multiple organ dysfunction syndrome (80.2% vs 78.2% vs 81.0%; p = 0.57) or prediction of new or progressive multiple organ dysfunction syndrome (84.8% vs 82.8% vs 80.3%; p = 0.26) for attendings, fellows, and residents/nurse practitioners, respectively. There was a weak correlation between the confidence and accuracy of prediction (pairwise correlation coefficient, 0.26; p < 0.001). CONCLUSIONS: PICU clinicians correctly identified multiple organ dysfunction syndrome and predicted new or progressive multiple organ dysfunction syndrome with 80% accuracy. However, only 8% of patients developed new or progressive multiple organ dysfunction syndrome, so accuracy was largely due to true negative predictions. The positive predictive value for new or progressive multiple organ dysfunction syndrome prediction was just 22%. Accuracy did not differ by clinician type, but was correlated with self-rated confidence and was higher for negative predictions.

Informed Family Member Involvement to Improve the Quality of Dementia Care in Nursing Homes.

OBJECTIVES: To describe the extent to which nursing homes engaged families in antipsychotic initiation decisions in the year before surveyor guidance revisions were implemented. DESIGN: Mixed-methods study based on semistructured interviews. SETTING: U.S. nursing homes (N = 20) from five CMS regions (III, IV, VI, VIII, IX). PARTICIPANTS: Family members of nursing home residents (N = 41). MEASUREMENTS: Family member responses to closed- and open-ended questions regarding involvement in resident care and antipsychotic initiation. Two researchers used a content analytical approach to code open responses to themes of family involvement in behavior management, decision-making, knowledge of risks and benefits, and informed consent. RESULTS: Fifty-four percent of family members felt highly involved in decisions about behavior management. Forty-two percent recalled being asked how to manage resident behavior without medication, and 17% recalled receipt of information about antipsychotic risks and benefits. Sixty-six percent felt highly involved in the process of initiating antipsychotic medication; 24% reported being asked for input into the antipsychotic initiation decision and knowing before the antipsychotic was started. CONCLUSION: Under existing federal regulations but before guidance revisions were implemented in 2013, more than 40% of families reported being involved in nonpharmacological behavior management of family members, but fewer than one in four reported being involved throughout the entire antipsychotic prescribing process. Interventions that standardize family engagement and promote adherence to existing federal regulations are needed. This discussion builds on these findings to weigh the policy options of greater enforcement of existing regulations versus enactment of new legislation to address this challenging issue.

Approaches to Gradual Dose Reduction of Chronic Off-Label Antipsychotics Used for Behavioral and Psychological Symptoms of Dementia.

OBJECTIVE: Little is known about how to best taper antipsychotics used in patients with dementia. To address this gap, we reviewed published antipsychotic discontinuation trials to summarize what is known about tapering strategies for antipsychotics used with older adults with dementia. We further developed pharmacokinetic-based gradual dose reduction (GDR) protocols based on antipsychotic half-lives. DATA SOURCES: MEDLINE, EMBASE, and International Pharmaceutical Abstracts were searched up to October 2014 to identify intervention studies reporting the behavioral and psychological symptoms of dementia outcomes resulting from discontinued off-label use of antipsychotics in nursing facility populations. Recently published pharmacokinetic reviews and standard pharmacology texts were used to determine antipsychotic drug half-lives for the pharmacokinetic-based GDR protocols. STUDY SELECTION: For the review, studies with an intervention resulting in antipsychotic medication discontinuation or tapering were eligible, including randomized controlled trials and pre- and post-intervention studies. DATA EXTRACTION: When available, we extracted the protocols used for antipsychotic GDR from each study included in the review. DATA SYNTHESIS: We found that clinical trials used different approaches to antipsychotic discontinuation, including abrupt discontinuation, slow tapers (more than two weeks), and mixed strategies based on drug dosage. None of the published trials described an approach based on pharmacokinetic principles. We developed a two-stage GDR protocol for tapering antipsychotic medications based on the log dose-response relationship; each stage was designed to result in a 50% dose reduction prior to discontinuation. This pharmacologically based strategy for patients chronically prescribed antipsychotics resulted in recommendations for slow tapers. CONCLUSION: Our theoretically derived GDR recommendations suggest a different approach than previously published in clinical trials. Further study is needed to evaluate the effect of this approach on patients.