SummaryBackground and objectives At least four definitions of AKI have recently been proposed. This study sought to characterize the epidemiology of AKI according to the most recent consensus definition proposed by the Kidney Disease Improving Global Outcomes (KDIGO) Work Group, and to compare it with three other definitions.Design, setting, participants, & measurements This was a retrospective cohort study of 31,970 hospitalizations at an academic medical center in 2010. AKI was defined and staged according to KDIGO criteria, the Acute Dialysis Quality Initiative's RIFLE criteria, the Acute Kidney Injury Network (AKIN) criteria, and a definition based on a model of creatinine kinetics (CK). Outcomes of interest were incidence, in-hospital mortality, length of stay, costs, readmission rates, and posthospitalization disposition.Results AKI incidence was highest according to the KDIGO definition (18.3%) followed by the AKIN (16.6%), RIFLE (16.1%), and CK (7.0%) definitions. AKI incidence appeared markedly higher in those with low baseline serum creatinine according to the KDIGO, AKIN, and RIFLE definitions, in which AKI may be defined by a 50% increase over baseline. AKI according to all definitions was associated with a significantly higher risk of death and higher resource utilization. The adjusted odds ratios for in-hospital mortality in those with AKI were highest with the CK definition (5.2; 95% confidence interval [95% CI], 4.1 to 6.6), followed by the RIFLE (2.9; 95% CI, 2.2 to 3.6), KDIGO (2.8; 95% CI, 2.2 to 3.6), and AKIN (2.6; 95% CI, 2.0 to 3.3) definitions. Concordance in diagnosis and staging was high among the KDIGO, AKIN, and RIFLE definitions. ConclusionsThe incidence of AKI in hospitalized individuals varies depending on the definition used. AKI according to all definitions is associated with higher in-hospital mortality and resource utilization. AKI may be inappropriately diagnosed in those with low baseline serum creatinine using definitions that incorporate percentage increases over baseline.

Pharmacotranscriptomics has become a powerful approach for evaluating the therapeutic efficacy of drugs and discovering new drug targets. Recently, studies of traditional Chinese medicine (TCM) have increasingly turned to high-throughput transcriptomic screens for molecular effects of herbs/ingredients. And numerous studies have examined gene targets for herbs/ingredients, and link herbs/ingredients to various modern diseases. However, there is currently no systematic database organizing these data for TCM. Therefore, we built HERB, a high-throughput experiment- and reference-guided database of TCM, with its Chinese name as BenCaoZuJian. We re-analyzed 6164 gene expression profiles from 1037 high-throughput experiments evaluating TCM herbs/ingredients, and generated connections between TCM herbs/ingredients and 2837 modern drugs by mapping the comprehensive pharmacotranscriptomics dataset in HERB to CMap, the largest such dataset for modern drugs. Moreover, we manually curated 1241 gene targets and 494 modern diseases for 473 herbs/ingredients from 1966 references published recently, and cross-referenced this novel information to databases containing such data for drugs. Together with database mining and statistical inference, we linked 12 933 targets and 28 212 diseases to 7263 herbs and 49 258 ingredients and provided six pairwise relationships among them in HERB. In summary, HERB will intensively support the modernization of TCM and guide rational modern drug discovery efforts. And it is accessible through http://herb.ac.cn/.

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BackgroundHyperuricemia has been reported to be associated with chronic kidney disease (CKD). However whether an elevated serum uric acid level is an independent risk factor for new-onset CKD remained controversial.MethodsA systematic review and meta-analysis using a literature search of online databases including PubMed, Embase, Ovid and ISI Web/Web of Science was conducted. Summary adjusted odds ratios with corresponding 95% confidence intervals (95% CI) were calculated to evaluate the risk estimates of hyperuricemia for new-onset CKD.ResultsThirteen studies containing 190,718 participants were included. A significant positive association was found between elevated serum uric acid levels and new-onset CKD at follow-up (summary OR, 1.15; 95% CI, 1.05–1.25). Hyperuricemia was found be an independent predictor for the development of newly diagnosed CKD in non-CKD patients (summary OR, 2.35; 95% CI, 1.59–3.46). This association increased with increasing length of follow-up. No significant differences were found for risk estimates of the associations between elevated serum uric acid levels and developing CKD between males and females.ConclusionsWith long-term follow-up of non-CKD individuals, elevated serum uric acid levels showed an increased risk for the development of chronic renal dysfunction.