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To investigate the pharmacodynamic properties of inclisiran, a small interfering RNA targeting proprotein convertase subtilisin-kexin type 9 (PCSK9), in individuals with normal renal function and renal impairment (RI). The analysis included participants with normal renal function and mild, moderate, and severe RI from the phase 1 ORION-7 renal study (n=31) and the phase 2 ORION-1 study (n=247) who received 300 mg of inclisiran sodium or placebo. In ORION-7, PCSK9 values were reduced at day 60 in the normal renal function group (68.1%±12.4%), mild RI group (74.2%±12.3%), moderate RI group (79.8%±4.9%), and severe RI group (67.9%±16.4%) (P<.001 vs placebo in all groups). Low-density lipoprotein cholesterol levels were significantly reduced versus placebo: normal renal function, 57.6%±10.7%; mild RI, 35.1%±13.5%; moderate RI, 53.1%±21.3%; severe RI, 49.2%±26.6% (P<.001 for all). In ORION-1, PCSK9 level reductions at day 180 were 48.3% to 58.6% in the 300-mg single-dose groups and 67.3% to 73.0% in the 300-mg 2-dose groups (P<.001 vs placebo in all groups). The corresponding low-density lipoprotein cholesterol level reductions were 35.7% to 40.2% in the 300-mg single-dose groups and 50.9% to 58.0% in the 300 mg 2-dose groups (P<.001 vs placebo in all groups). In ORION-7, exposure to inclisiran was proportionally greater in individuals with increasing RI; inclisiran was undetectable in plasma 48 hours after administration in any group. The pharmacodynamic effects and safety profile of inclisiran were similar in study participants with normal and impaired renal function. Dose adjustments of inclisiran are not required in these patients. clinicaltrials.gov Identifiers: NCT02597127 and NCT03159416

Chronic kidney disease is an important concern in preventive medicine, but the rate of decline in renal function in healthy population is not well defined. The purpose of this study was to determine reference values for the estimated glomerular filtration rate (eGFR) and rate of decline of eGFR in healthy subjects and to evaluate factors associated with this decline using a large cohort in Japan. Retrospective cross-sectional and longitudinal studies were performed with healthy subjects aged ≥18 years old who received a medical checkup. Reference values for eGFR were obtained using a nonparametric method and those for decline of eGFR were calculated by mixed model analysis. Relationships of eGFR decline rate with baseline variables were examined using a linear least-squares method. In the cross-sectional study, reference values for eGFR were obtained by gender and age in 72,521 healthy subjects. The mean (±SD) eGFR was 83.7±14.7 ml/min/1.73 m2. In the longitudinal study, reference values for eGFR decline rate were obtained by gender, age, and renal stage in 45,586 healthy subjects. In the same renal stage, there was little difference in the rate of decline regardless of age. The decline in eGFR depended on the renal stage and was strongly related to baseline eGFR, with a faster decline with a higher baseline eGFR and a slower decline with a lower baseline eGFR. The mean (±SD) eGFR decline rate was ‒1.07±0.42 ml/min/1.73 m2/year (‒1.29±0.41%/year) in subjects with a mean eGFR of 81.5±11.6 ml/min/1.73 m2. The present study clarified for the first time the reference values for the rate of eGFR decline stratified by gender, age, and renal stage in healthy subjects. The rate of eGFR decline depended mainly on baseline eGFR, but not on age, with a slower decline with a lower baseline eGFR.

PurposeFedratinib (SAR302503, TG101348) is an orally administered Janus kinase (JAK) 2-selective inhibitor that is being developed for the treatment of patients with myelofibrosis (MF). The objectives of this analysis were to develop a population pharmacokinetic (PK) model to characterize fedratinib concentration-time profiles in patients with MF, polycythemia vera (PV) and essential thrombocythemia (ET) following oral fedratinib administration; and to investigate the effects of selected covariates on fedratinib PK parameters.MethodsNonlinear mixed effects modeling was employed in developing a population PK model for fedratinib. Intensive or sparse fedratinib concentration data collected in adult subjects with MF, PV or ET from six studies were pooled, and a total of 452 subjects and 3442 plasma concentration observations were included in the final model.ResultsFedratinib PK in patients with MF/PV/ET was adequately described by a two-compartment structural PK model with first-order absorption incorporating a lag time and first-order elimination. Following oral administration, fedratinib undergoes biphasic disposition and exhibits linear, time-invariant PK at doses of 200 mg and above. Compared to MF/ET patients, PV patients had higher apparent clearance (CL/F) and apparent central volume of distribution. Creatinine clearance was a statistically significant covariate on CL/F, and patients with mild and moderate renal impairment had 10% and 37% increases in fedratinib exposure as compared to patients with normal renal function. No clinically meaningful effect on fedratinib exposure was observed regarding age, body weight, sex, race and liver function.ConclusionsThese results should serve as the basis for dose adjustment of fedratinib for special populations.

Estimators of glomerular filtration rate (GFR) have been shown to be flawed in critically ill patients, especially for augmented renal clearance (ARC), commonly defined as a measured urinary creatinine clearance (CrCl) ≥ 130 ml/min/1.73 m2 [1]. [...]measuring CrCl should be performed in daily practice on the intensive care unit (ICU). [...]the aim of this study is to define the most precise GFR estimator, which can then be used to detect ARC when measured CrCl is unavailable. [...]the performance of these cut-offs was evaluated in an external single-center (Leuven, January 2016–December 2016) validation set by receiver-operating characteristics (ROC) curve analysis, using 2000 bootstrap replicates.

Background Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease and is characterized by gradual cyst growth and expansion, increase in kidney volume with an ultimate decline in kidney function leading to end stage renal disease (ESRD). Given the decades long period of stable kidney function while cyst growth occurs, it is important to identify those patients who will progress to ESRD. Recent data from our and other laboratories have demonstrated that metabolic reprogramming may play a key role in cystic epithelial proliferation resulting in cyst growth in ADPKD. Height corrected total kidney volume (ht-TKV) accurately reflects cyst burden and predicts future loss of kidney function. We hypothesize that specific plasma metabolites will correlate with eGFR and ht-TKV early in ADPKD, both predictors of disease progression, potentially indicative of early physiologic derangements of renal disease severity. Methods To investigate the predictive role of plasma metabolites on eGFR and/or ht-TKV, we used a non-targeted GC-TOF/MS-based metabolomics approach on hypertensive ADPKD patients in the early course of their disease. Patient data was obtained from the HALT-A randomized clinical trial at baseline including estimated glomerular filtration rate (eGFR) and measured ht-TKV. To identify individual metabolites whose intensities are significantly correlated with eGFR and ht-TKV, association analyses were performed using linear regression with each metabolite signal level as the primary predictor variable and baseline eGFR and ht-TKV as the continuous outcomes of interest, while adjusting for covariates. Significance was determined by Storey’s false discovery rate (FDR) q-values to correct for multiple testing. Results Twelve metabolites significantly correlated with eGFR and two triglycerides significantly correlated with baseline ht-TKV at FDR q-value < 0.05. Specific significant metabolites, including pseudo-uridine, indole-3-lactate, uric acid, isothreonic acid, and creatinine, have been previously shown to accumulate in plasma and/or urine in both diabetic and cystic renal diseases with advanced renal insufficiency. Conclusions This study identifies metabolic derangements in early ADPKD which may be prognostic for ADPKD disease progression. Clinical trial HALT Progression of Polycystic Kidney Disease (HALT PKD) Study A; Clinical www.clinicaltrials.gov identifier: NCT00283686; first posted January 30, 2006, last update posted March 19, 2015.

In clinical practice, the glomerular filtration rate (GFR), a measurement of kidney functioning, is normally calculated using equations, such as the European Kidney Function Consortium (EKFC) equation. Despite being the most general equation, EKFC, just like previously proposed approaches, can still struggle to achieve satisfactory performance, limiting its clinical applicability. As a possible solution, recently machine learning (ML) has been investigated to improve GFR prediction, nonetheless the literature still lacks a general and multi-center study. Using a dataset with 19,629 patients from 13 cohorts, we investigate if ML can improve GFR prediction in comparison to EKFC. More specifically, we compare diverse ML methods, which were allowed to use age, sex, serum creatinine, cystatin C, height, weight and BMI as features, in internal and external cohorts against EKFC. The results show that the most performing ML method, random forest (RF), and EKFC are very competitive where RF and EKFC achieved respectively P10 and P30 values of 0.45 (95% CI 0.44;0.46) and 0.89 (95% CI 0.88;0.90), whereas EKFC yielded 0.44 (95% CI 0.43; 0.44) and 0.89 (95% CI 0.88; 0.90), considering the entire cohort. Small differences were, however, observed in patients younger than 12 years where RF slightly outperformed EKFC.

Fish oil has been used effectively in the treatment of cardiovascular disease via triglyceride reduction and inflammation modulation. This study aimed to assess the effects of fish oil on patients with nonalcoholic fatty liver disease (NAFLD) associated with hyperlipidemia. Eighty participants with NAFLD associated with hyperlipidemia were randomly assigned to consume fish oil (n=40, 4 g/d) or corn oil capsules (n=40, 4 g/d) for 3 months in a double-blind, randomized clinical trial. Blood levels of lipids, glucose and insulin, liver enzymes, kidney parameters and cytokines at baseline and the end of the study were measured. Seventy people finished the trial. Plasma concentrations of eicosapentaenoic acid and docosahexaenoic acid significantly increased in the fish oil group after intervention. After adjustment for age, gender and BMI, fish oil significantly decreased fasting serum concentrations of total cholesterol, triglyceride, apolipoprotein B and glucose (by (mean±SD) 0.49±0.43 mmol/L, 0.58±0.89 mmol/L, 0.28±0.33 g/L and 0.76±0.56 mmol/L, respectively, P<0.05), as well as alanine aminotransferase and γ-glutamyl transpeptidase levels (by (median (interquartile)) 9.0(0.5, 21.5) and 7.0(2.2, 20.0) IU/L, respectively, P<0.05), significantly increased serum adiponectin levels (by 1.29±0.62 μg/mL, P<0.001), and reduced serum levels of tumor necrosis factor α, leukotrienes B4, fibroblast growth factor 21 (FGF21), cytokeratin 18 fragment M30 and prostaglandin E2 (by 1.70±1.18 pg/mL, 0.59±0.28 ng/mL, 121±31 pg/mL, 83±60 IU/L and 10.9±2.3 pg/mL, respectively, P<0.001). Corn oil had no effect except for increasing serum creatinine concentrations by 7.7±8.9 μmol/L (P=0.008). The effects of fish oil on lipids, glucose and γ-glutamyl transpeptidase were positively correlated with the reductions of serum FGF21 and prostaglandin E2 concentrations after adjustment for age, gender and BMI (r = 0.275 to 0.360 and 0.261 to 0.375, respectively, P<0.05). In conclusion, our findings suggest that fish oil can benefit metabolic abnormalities associated with NAFLD treatment. ChiCTR-TRC-12002380.

Background Sepsis is common and frequently fatal condition in critically ill patients and is a major cause of acute kidney injury (AKI). In this retrospective study, we sought to develop a comprehensive risk score model of sepsis associated-AKI (SA-AKI). Methods A total of 2617 patients were randomly assigned to a development (1554 patients) and a validation group (777 patients). The risk score model for SA-AKI was developed with multivariate regression analysis in development group and the model was further evaluated on validation group. Results We identified 16 independent predictors of SA-AKI in development group (age ≥ 60 years, hypertension/coronary heart disease, diabetes, chronic kidney disease, heart failure, chronic obstructive pulmonary disease, acute severe pancreatitis, hypotension, hypoproteinemia, lactic acidosis, the length of stay in intensive care unit(ICU), 60 g/L

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