Whether preoperative proteinuria associates with adverse renal outcomes after cardiac surgery is unknown. Here, we performed a secondary analysis of a prospectively enrolled cohort of adult patients undergoing coronary artery bypass grafting (CABG) at a medical center and its two affiliate hospitals between 2003 and 2007. We excluded patients with stage 5 CKD or those who received dialysis previously. We defined proteinuria, measured with a dipstick, as mild (trace to 1ϩ) or heavy (2ϩ to 4ϩ). Among a total of 1052 patients, cardiac surgery-associated acute kidney injury (CSA-AKI) developed in 183 (17.4%) patients and required renal replacement therapy (RRT) in 50 (4.8%) patients. In a multiple logistic regression model, mild and heavy proteinuria each associated with an increased odds of CSA-AKI, independent of CKD stage and the presence of diabetes mellitus (mild: OR 1.66, 95% CI 1.09 to 2.52; heavy: OR 2.30, 95% CI 1.35 to 3.90). Heavy proteinuria also associated with increased odds of postoperative RRT (OR 7.29, 95% CI 3.00 to 17.73). In summary, these data suggest that preoperative proteinuria is a predictor of CSA-AKI among patients undergoing CABG.

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AimsThe influences of nonstationarity and nonlinearity on heart rate time series can be mathematically qualified or quantified by multiscale entropy (MSE). The aim of this study is to investigate the prognostic value of parameters derived from MSE in the patients with systolic heart failure.Methods and ResultsPatients with systolic heart failure were enrolled in this study. One month after clinical condition being stable, 24-hour Holter electrocardiogram was recording. MSE as well as other standard parameters of heart rate variability (HRV) and detrended fluctuation analysis (DFA) were assessed. A total of 40 heart failure patients with a mea age of 56±16 years were enrolled and followed-up for 684±441 days. There were 25 patients receiving β-blockers treatment. During follow-up period, 6 patients died or received urgent heart transplantation. The short-term exponent of DFA and the slope of MSE between scale 1 to 5 were significantly different between patients with or without β-blockers (p = 0.014 and p = 0.028). Only the area under the MSE curve for scale 6 to 20 (Area6–20) showed the strongest predictive power between survival (n = 34) and mortality (n = 6) groups among all the parameters. The value of Area6–20 21.2 served as a significant predictor of mortality or heart transplant (p = 0.0014).ConclusionThe area under the MSE curve for scale 6 to 20 is not relevant to β-blockers and could further warrant independent risk stratification for the prognosis of CHF patients.

In this study, we performed a comprehensively analysis of gene expression and DNA methylation data to establish diagnostic, prognostic, and recurrence models for hepatocellular carcinoma (HCC).Methods: We collected gene expression and DNA methylation datasets for over 1,200 clinical samples. Integrated analyses of RNA-sequencing and DNA methylation data were performed to identify DNA methylation-driven genes. These genes were utilized in univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to build a prognostic model. Recurrence and diagnostic models for HCC were also constructed using the same genes.Results: A total of 123 DNA methylation-driven genes were identified. Two of these genes (SPP1 and LCAT) were chosen to construct the prognostic model. The high-risk group showed a markedly unfavorable prognosis compared to the low-risk group in both training (HR = 2.81; P < 0.001) and validation (HR = 3.06; P < 0.001) datasets. Multivariate Cox regression analysis indicated the prognostic model to be an independent predictor of prognosis (P < 0.05). Also, the recurrence model successfully distinguished the HCC recurrence rate between the high-risk and low-risk groups in both training (HR = 2.22; P < 0.001) and validation (HR = 2; P < 0.01) datasets. The two diagnostic models provided high accuracy for distinguishing HCC from normal samples and dysplastic nodules in the training and validation datasets, respectively.Conclusions: We identified and validated prognostic, recurrence, and diagnostic models that were constructed using two DNA methylation-driven genes in HCC. The results obtained by integrating multidimensional genomic data offer novel research directions for HCC biomarkers and new possibilities for individualized treatment of patients with HCC.

IVM is a feasible treatment for women with PCOS. FSH priming has no additional beneficial effect on IVM.