Introduction In intensive care unit (ICU) patients, delirium is frequent, occurs early in ICU admission, and is associated with poor outcomes. Risk models based on clinical factors have shown variable performance in terms of predictive ability. Identification of a candidate biomarker that associates with delirium may lead to a better understanding of disease mechanism, validation biomarker studies, and the ability to develop targeted interventions for prevention and treatment of delirium. This study analyzed metabolite concentrations early in the course of ICU admission to assess the association with delirium onset. Methods Within 24 hours of ICU admission, blood samples for global and targeted metabolomics analyses in adult surgical ICU patients were collected prospectively. Metabolites were determined using mass spectrometry/ultra‐high‐pressure liquid chromatography and analyzed in patients with delirium and a group of controls matched on age, sex, and admission Sequential Organ Function Assessment (SOFA) score. Results Patients in the study (65 per group) were a mean age of 59 years, had a median SOFA score of 6, and were most commonly admitted to the ICU following major trauma. In the delirium group, median onset of delirium was 3 (interquartile range 1–6) days, and the most common delirium subtype was mixed (56%). Kynurenic acid was significantly increased, and tryptophan concentration was significantly decreased in the delirium group (p=0.04). The ratio of kynurenine‐to‐tryptophan concentration was significantly higher in the delirium group (p=0.005). Conclusions Evidence of upregulation was found in the tryptophan metabolic pathway in delirious patients because tryptophan concentrations were lower, tryptophan metabolites were higher, and the kynurenine‐to‐tryptophan ratio was increased. These findings suggest a role of increased inflammation and accumulation of neurotoxic metabolites in the pathogenesis of ICU delirium. Future studies should target this pathway to validate metabolites in the tryptophan pathway as risk biomarkers in patients with ICU delirium.
ABSTRACT Although several dosage adjustment regimens have been proposed, there is little quantitative information to guide the initiation of ceftazidime therapy in patients who are receiving continuous renal replacement therapy. To determine the clearance of ceftazidime by continuous venovenous hemofiltration (CVVH) and continuous venovenous hemodialysis (CVVHD), we performed controlled clearance studies with stable hemodialysis patients with three hemofilters: a 0.6-m 2 acrylonitrile copolymer (AN69; Hospal) filter, a 2.1-m 2 polymethylmethacrylate filter (PMMA; Toray) filter and a 0.65-m 2 polysulfone (PS; Fresenius) filter. Subjects received 1,000 mg of ceftazidime intravenously prior to the start of a clearance study. The concentration of ceftazidime in multiple plasma and dialysate or ultrafiltrate samples was determined by high-performance liquid chromatography. The diffusional clearances (CI diffusion ) and sieving coefficients of ceftazidime were compared by a mixed-model repeated-measures analysis of variance with filter and blood, dialysate inflow, or ultrafiltration rate as the main effect and the patient as a random effect. The fraction of ceftazidime bound to plasma proteins was 17% ± 7% (range, 10 to 25%). The clearances of ceftazidime, urea, and creatinine by CVVHD were essentially constant at blood flow rates of 75 to 250 ml/min for all three filters. Significant linear relationships ( P < 0.0001) were observed between CI diffusion of ceftazidime and clearance of urea for all three filters: AN69 (slope = 0.83), PMMA (slope = 0.89), and PS (slope = 1.03). Ceftazidime clearance was membrane independent during CVVH and CVVHD. CVVH and CVVHD can significantly augment the clearance of ceftazidime. Dosing strategies for initiation of ceftazidime therapy in patients receiving CVVH and CVVHD are proposed.
Beverage-drug interactions have remained an active area of research and have been the subject of extensive investigations in the past 2 decades. The known mechanisms of clinically relevant beverage-drug interactions include modulation of the activity of cytochrome P450 (CYP) 3A and organic anion-transporting polypeptide (OATP). For CYP3A-mediated beverage-drug interaction, the in vivo CYP3A inhibitory effect is limited to grapefruit juice (GFJ), which increases the bioavailability of several orally administered drugs that undergo extensive first-pass metabolism via enteric CYP3A. In contrast, clinically significant OATP-mediated beverage-drug interactions have been observed with not only GFJ but also orange juice, apple juice, and, most recently, green tea. Fruit juices and green tea are all a mixture of a large number of constituents. The investigation of specific constituent(s) responsible for the enzyme and/or transporter inhibition remains an active area of research, and many new findings have been obtained on this subject in the past several years. This review highlights the multiple mechanisms through which beverages can alter drug disposition and provides an update on the new findings of beverage-drug interactions, with a focus on fruit juices and green tea.
1 The disposition of nalmefene was evaluated in young and elderly normal healthy volunteers. Subjects received either a single 1 mg ( n =18 young; n =11 elderly) or 2 mg ( n =8 young; n =15 elderly) intravenous bolus dose of nalmefene. 2 Following the administration of nalmefene, the initial plasma concentrations were significantly higher in elderly vs young subjects. The higher concentrations were the result of the 30 to 40% smaller central compartment apparent volume of distribution that was observed in the elderly subjects as compared with the young volunteers (2.8±1.1 vs 3.9±1.1 l kg −1 for 1 mg dose). The elderly volunteers also had a significantly shorter distributional half‐life ( t1/2λ1 ) than young volunteers (0.7±0.7 vs 1.3±0.8 h for 1 mg dose). No significant differences between groups were observed for the elimination half‐life, clearance or steady‐state apparent volume of distribution. 3 Although transiently higher nalmefene plasma concentrations were observed in the elderly immediately following drug administration, there was no association between this observation and adverse events. We conclude that no dosage alteration is warranted in elderly patients.
Pioglitazone is the most widely used thiazolidinedione and acts as an insulin-sensitizer through activation of the Peroxisome Proliferator-Activated Receptor-γ (PPARγ). Pioglitazone is approved for use in the management of type 2 diabetes mellitus (T2DM), but its use in other therapeutic areas is increasing due to pleiotropic effects. In this hypothesis article, the current clinical evidence on pioglitazone pharmacogenomics is summarized and related to variability in pioglitazone response. How genetic variation in the human genome affects the pharmacokinetics and pharmacodynamics of pioglitazone was examined. For pharmacodynamic effects, hypoglycemic and anti-atherosclerotic effects, risks of fracture or edema, and the increase in body mass index in response to pioglitazone based on genotype were examined. The genes CYP2C8 and PPARG are the most extensively studied to date and selected polymorphisms contribute to respective variability in pioglitazone pharmacokinetics and pharmacodynamics. We hypothesized that genetic variation in pioglitazone pathway genes contributes meaningfully to the clinically observed variability in drug response. To test the hypothesis that genetic variation in PPARG associates with variability in pioglitazone response, we conducted a meta-analysis to synthesize the currently available data on the PPARG p.Pro12Ala polymorphism. The results showed that PPARG 12Ala carriers had a more favorable change in fasting blood glucose from baseline as compared to patients with the wild-type Pro12Pro genotype (p = 0.018). Unfortunately, findings for many other genes lack replication in independent cohorts to confirm association; further studies are needed. Also, the biological functionality of these polymorphisms is unknown. Based on current evidence, we propose that pharmacogenomics may provide an important tool to individualize pioglitazone therapy and better optimize therapy in patients with T2DM or other conditions for which pioglitazone is being used.
