Band 35, Heft 1

Background Despite the well-studied safety profile of dabigatran, its interactions with genetic polymorphism parameters are poorly understood, especially in patients with moderate chronic kidney disease (CKD). The study assessed whether genetic factors can contribute to CKD and alter dabigatran concentration. Methods Patients with atrial fibrillation (AF) and stage 3 CKD treated with dabigatran 110 or 150 mg have been included in the study. Real-time polymerase chain reaction was used to evaluate single-nucleotide polymorphisms of the ABCB1 gene ( rs1045642 and rs4148738 ) and CES1 gene ( rs2244613 ). A plasma trough concentration/dose (C/D) ratio was used as a pharmacokinetic index. Results A total of 96 patients aged 51–89 years (median age: 75 years) were evaluated. Patients on a reduced regimen of 110 mg twice a day were older (79.8 vs. 67.9, p < 0.0001) and had lower creatinine clearance (49.7 vs. 62.3 mL/min/1.73 m 2 , p = 0.015). Patients with the rs2244613 CC genotype had lower C/D values (70% reduction in the mean C/D vs. AA genotype, p = 0.001). Linear stepwise regression has shown the CKD epidemiology collaboration to be the only significant predictor of C/D among genetic factors and kidney function characteristics. During the median follow-up of 15 months, there were 15 bleedings in 13 patients. Conclusions Polymorphism of CES1 rs2244613 can contribute to the safety of dabigatran in patients with AF and CKD. There was no influence of the aforementioned polymorphisms of ABCB1 on dabigatran trough plasma concentrations and C/D. Kidney function is a mainstay of clinical decision-making on direct oral anticoagulant (DOAC) dose, and further knowledge should be accumulated on the role of genetic factors.

Background Hospitalized pediatric patients are at an increased risk of experiencing potential drug-drug interactions (pDDIs) due to polypharmacy and the unlicensed and off-label administration of drugs. The aim of this study is to characterize clinically significant pDDIs in pediatric patients hospitalized in a tertiary respiratory center. Methods A retrospective analysis of medications prescribed to pediatric patients admitted to the pediatric ward (PW) and pediatric intensive care unit (PICU) of a respiratory referral center was carried out over a six-month period. The pDDIs were identified using the Lexi-Interact database and considered as clinically relevant according to the severity rating as defined in the database. Frequency, drug classes, mechanisms, clinical managements, and risk factors were recorded for these potential interactions. Results Eight hundred and forty-five pDDIs were identified from the analysis of 176 prescriptions. Of the total pDDIs, 10.2% in PW and 14.6% in PICU were classified as clinically significant. Anti-infective agents and central nervous system drugs were the main drug classes involved in clinically significant pDDIs as object and/or precipitant drugs. A higher number of medications [odds ratio (OR): 4.8; 95% confidence interval (CI): 2.0–11.4; p < 0.001] and the existence of a nonrespiratory disease, which led to a respiratory disorder (OR: 3.8; 95% CI: 1.40–10.4; p < 0.05), were the main risk factors associated with an increased incidence of pDDIs. Conclusions A high and similar risk of pDDIs exists in pediatric patients with respiratory disorders hospitalized in PW and PICU. The patients prescribed a higher number of medications and presenting respiratory symptoms induced by a nonrespiratory disease require extra care and monitoring. Pediatricians should be educated about clinically significant DDIs for highly prescribed medications in their settings in order to take preventive measures and safeguard patient safety.

Background Probiotics are live microbial organisms that provide benefit to the host while co-habitating in the gastrointestinal tract. Probiotics are safe, available over the counter, and have clinical benefit by reducing the number of antibiotic-associated diarrhea days. Prescriptions from providers and direct consumer demand of probiotics appear to be on the rise. Several recent animal studies have demonstrated that probiotics may have significant effect on absorption of co-administered drugs. However, to date, most probiotic-drug interaction studies in animal models have been limited to bacterial probiotics and nonantibiotic drugs. Methods We performed a traditional pharmacokinetic mouse study examining the interactions between a common commercially available yeast probiotic, Saccharomyces boulardii CNCM I-745 (Florastor ® ) and an orally administered amoxicillin. Results We showed that there were no significant differences in pharmacokinetic parameters (half-life, area under the curve, peak concentrations, time to reach maximum concentration, elimination rate constant) of amoxicillin between the probiotic treated and untreated control groups. Conclusions Altogether, our findings suggest that coadministration or concurrent use of S. boulardii probiotic and amoxicillin would not likely alter the efficacy of amoxicillin therapy.

Background Diazepam is one of the most commonly prescribed tranquilizers for therapy of alcohol withdrawal syndrome (AWS). Despite its popularity, there is currently no precise information on the effect of genetic polymorphisms on its efficacy and safety. The objective of our study was to investigate the effect of CYP2C19*2 and CYP2C19*17 genetic polymorphisms on the efficacy and safety of diazepam in patients with AWS. Methods The study was conducted on 30 Russian male patients suffering from the AWS who received diazepam in injections at a dosage of 30.0 mg/day for 5 days. The efficacy and safety assessment was performed using psychometric scales and scales for assessing the severity of adverse drug reactions. Results Based on the results of the study, we revealed the differences in the efficacy of therapy in patients with different CYP2C19 681G>A ( CYP2C19*2 , rs4244285 ) genotypes: ( CYP2C19*1/*1 ) −8.5 [−15.0; −5.0], ( CYP2C19*1/*2 and CYP2C19*2/*2 ) −12.0 [−13.0; −9.0], p = 0.021. The UKU scale scores, which were used to evaluate the safety of therapy, were also different: ( CYP2C19*1/*1 ) 7.0 [6.0; 12.0], ( CYP2C19*1/*2 and CYP2C19*2/*2 ) 9.5 [8.0; 11.0], p = 0.009. Patients carrying different CYP2C19 –806C>T ( CYP2C19*17 , rs12248560 ) genotypes also demonstrated differences in therapy efficacy and safety rates. Conclusions Thus, the effects of CYP2C19*2 and CYP2C19*17 genetic polymorphisms on the efficacy of diazepam were demonstrated.

Background Evidence from the literature, highlights the increased risk of developing glucose intolerance and type 2 diabetes mellitus (T2DM) with statin therapy. In addition, few animal studies demonstrate that adipsin secreted from adipocytes plays a crucial role in insulin secretion and the development of T2DM. Methods To further explore the role of serum adipsin, in this prospective open label study, 55 newly diagnosed dyslipidemic patients were enrolled. Before starting statin therapy, liver function test (LFT), kidney function test (KFT), lipid profile, glycemic parameters [glycated hemoglobin A (HbA 1c ), fasting blood sugar (FBS), and postprandial blood sugar (PPBS)], serum insulin, and serum adipsin were estimated. Then these patients were prescribed statin (i.e. atorvastatin, rosuvastatin, or pitavastatin) and after 12 weeks of therapy, all the above investigations were repeated. Results After 12 weeks of statin therapy, the LFT and KFT values remained unchanged and lipid parameters showed significant improvement. But the glycemic parameters deranged significantly (p < 0.001), i.e. FBS, PPBS, and HbA 1c increased by 12.49% (102.99 ± 20.76 mg/dL), 24.72% (147.71 ± 47.29 mg/dL), and 21.43% (6.38 ± 1.34%), respectively. On the other hand, the baseline adipsin (2.73 ± 1.99 ng/mL) and insulin (16.13 ± 12.50 mIU/L) levels reduced significantly (p < 0.0001) to 1.43 ±1.13 ng/mL and 6.91 ± 5.93 mIU/L, respectively. The reduction in serum adipsin also showed a positive correlation with reduction in serum insulin ( r = 0.85; p < 0.0001). None of the patients experienced any significant adverse effect or reaction leading to discontinuation of therapy. Conclusions There might be an association between reduction in adipsin and development of glucose intolerance by statin therapy.