No abstract

Antiepileptic drugs (AEDs) are routinely prescribed for the management of a variety of neurologic and psychiatric conditions, including epilepsy and epilepsy syndromes. Physiologic changes due to aging, pregnancy, nutritional status, drug interactions, and diseases (ie, those involving liver and kidney function) can affect pharmacokinetics of AEDs. This review discusses foundational pharmacokinetic characteristics of AEDs currently available in the United States, including clobazam but excluding the other benzodiazepines. Commonalities of pharmacokinetic properties of AEDs are discussed in detail. Important differences among AEDs and clinically relevant pharmacokinetic interactions in absorption, distribution, metabolism, and/or elimination associated with AEDs are highlighted. In general, newer AEDs have more predictable kinetics and lower risks for drug interactions. This is because many are minimally or not bound to serum proteins, are primarily renally cleared or metabolized by non–cytochrome P450 isoenzymes, and/or have lower potential to induce/inhibit various hepatic enzyme systems. A clear understanding of the pharmacokinetic properties of individual AEDs is essential in creating a safe and effective treatment plan for a patient.

Nonhuman primates (NHPs) have provided robust experimental animal models for many human-related diseases due to their similar physiologies. Nonetheless, profound differences remain in the acquisition, progression, and outcome of important diseases such as AIDS and Alzheimer's, for which the underlying basis remains obscure. We explored the utility of human high-density oligonucleotide arrays to survey the transcription profile of NHP genomes. Total RNA from prefrontal cortices of human (Homo sapiens), common chimpanzee (Pan troglodytes), cynomolgous macaque (Macaca fascicularis), and common marmoset (Callithrix jacchus) was labeled and hybridized to Affymetrix U95A GeneChip probe arrays. Corresponding data obtained previously from common chimpanzee and orangutan (Pongo pygmaeus) were added for comparison. Qualitative (present or not detected) and quantitative (expression level) analysis indicated that many genes known to be involved in human neurological disorders were present and regulated in NHPs. A gene involved in dopamine metabolism (catechol-O-methyltransferase) was absent in macaque and marmoset. Glutamate receptor 2 was up-regulated, and transcription-associated genes were down-regulated in NHPs compared with humans. We demonstrate that transcript profiling of NHPs could provide comparative genomic data to validate and better focus experimental animal models of human neurological disorders.

Background Patients’ ability to accurately report their pre-admission medications is a vital aspect of medication reconciliation and may affect subsequent medication adherence and safety. Little is known about predictors of pre-admission medication understanding. Methods We conducted a cross-sectional evaluation of patients at 2 hospitals using a novel Medication Understanding Questionnaire (MUQ). MUQ scores range from 0 to 3 and test knowledge of the medication purpose, dose, and frequency. We used multivariable ordinal regression to determine predictors of higher MUQ scores. Results Among the 790 eligible patients, the median age was 61 (interquartile range [IQR] 52, 71), 21% had marginal or inadequate health literacy, and the median number of medications was 8 (IQR 5, 11). Median MUQ score was 2.5 (IQR 2.2, 2.8). Patients with marginal or inadequate health literacy had a lower odds of understanding their medications (odds ratio [OR]=0.53; 95% confidence interval [CI], 0.34 to 0.84; p=0.0001; and OR=0.49; 95% CI, 0.31 to 0.78; p=0.0001; respectively), compared to patients with adequate health literacy. Higher number of prescription medications was associated with lower MUQ scores (OR=0.52; 95% CI, 0.36 to 0.75; for those using 6 medications vs 1; p=0.0019), as was impaired cognitive function (OR=0.57; 95% CI, 0.38 to 0.86; p=0.001). Conclusions Lower health literacy, lower cognitive function, and higher number of medications each were independently associated with less understanding of the pre-admission medication regimen. Clinicians should be aware of these factors when considering the accuracy of patient-reported medication regimens and counseling patients about safe and effective medication use.

Background Clinical pharmacists who review medication orders can reduce potentially inappropriate medications (PIMs) in hospitalized elderly patients, but this approach may be inefficient for settings with high clinical volume. Design Pilot intervention. Setting Academic, tertiary care hospital. Participants Hospitalized geriatric patients, age 65 or older, admitted to General Medicine, Orthopedics, and Urology Services during a 3 week period in 2011 and who wereadministered at least one medication from a list of 240 PIMs. Intervention A computerized PIMS dashboard flagged patients with at least one administered PIM or a high calculated anticholinergic score. Additionally, the dashboard displayed 48-hour cumulative narcotic and benzodiazepine administration. Patients were ranked to reflect the estimated risk of an adverse event using logical combinations of data (e.g. use of multiple sedatives in a non-monitored location). In a pilot implementation, a clinical pharmacist reviewed the flagged patient records and delivered an immediate point-of-care intervention for the treating physician. Measurements Clinician response to pharmacist intervention. Results Of797 patients admitted over a three-week period, the PIMS dashboard flagged 179 patients (22%) and 485 patient-medication pairs for review by the clinical pharmacist. Seventy-one patient records with 139patient-medication pairs required additional manual review of the electronic medical record. Twenty-two patients receiving 40 inappropriate medication orders were judged to warrant an intervention, which was delivered by personal communication via phone or text message. Clinicians enacted 31 of 40 (78%) pharmacist recommendations. Conclusion An electronic PIMs dashboard provided an efficient mechanism for clinical pharmacists to rapidly screen the medication regimens of hospitalized elderly and deliver a timely point-of-care intervention when indicated.