ABSTRACT
BACKGROUND@#The early identification of heart failure (HF) risk may favorably affect outcomes, and the combination of multiple biomarkers may provide a more comprehensive and valuable means for improving the risk of stratification. This study was conducted to assess the importance of individual cardiac biomarkers creatine kinase MB isoenzyme (CK-MB), B-type natriuretic peptide (BNP), galectin-3 (Gal-3) and soluble suppression of tumorigenicity-2 (sST2) for HF diagnosis, and the predictive performance of the combination of these four biomarkers was analyzed using random forest algorithms.@*METHODS@#A total of 193 participants (80 patients with HF and 113 age- and gender-matched healthy controls) were included from June 2017 to December 2017. The correlation and regression analysis were conducted between cardiac biomarkers and echocardiographic parameters. The accuracy and importance of these predictor variables were assessed using random forest algorithms.@*RESULTS@#Patients with HF exhibited significantly higher levels of CK-MB, BNP, Gal-3, and sST2. BNP exhibited a good independent predictive capacity for HF (AUC 0.956). However, CK-MB, sST2, and Gal-3 exhibited a modest diagnostic performance for HF, with an AUC of 0.709, 0.711, and 0.777, respectively. BNP was the most important variable, with a remarkably higher mean decrease accuracy and Gini. Furthermore, there was a general increase in predictive performance using the multi-marker model, and the sensitivity, specificity was 91.5% and 96.7%, respectively.@*CONCLUSION@#The random forest algorithm provides a robust method to assess the accuracy and importance of predictor variables. The combination of CK-MB, BNP, Gal-3, and sST2 achieves improvement in prediction accuracy for HF.
Subject(s)
Adult , Female , Humans , Male , Middle Aged , Algorithms , Biomarkers , Blood , Metabolism , Creatine Kinase, MB Form , Blood , Metabolism , Echocardiography , Galectin 3 , Blood , Metabolism , Heart Failure , Blood , Metabolism , Pathology , Natriuretic Peptide, Brain , Blood , MetabolismABSTRACT
To analyze the genetic characterization of epidemic rubella virus strains isolated in Liaoning from 2007-2012, a total of 145 rubella virus strains were isolated using Vero/Slam cell line from the patients' throat swabs during rubella outbreaks and sporadics cases in Liaoning Province from 2007 to 2012. Fragments of 945 nucleotides containing 1E gene from 145 rubella virus isolates were amplified by RT-PCR, the PCR products were sequenced and analyzed. Based on the 739 nucleotides of 1E gene, the phylogenetic trees were constructed with 32 WHO rubella reference strains of 13 genotypes downloaded from GenBank and 145 rubella virus strains. The results showed that the 145 rubella virus strains in 2007 -2012 belonged to genotype 1E, nucleotide acids and amino acids similarities were 97.2%-100.0% and 97.6%-100.0%, respectively. Compared to the 1E reference strains(Rvi/ Dezhou.CHN/02, RVi/MYS/01), the nucleotide acids and amino acids similarities were 96.6%-99.2% and 98.2%-100.0%, respectively except for one amino acid change (Val246-Ala246) of RVi/Shenyang. Liaoning. CHN/13.11/13, and Asp262-Asn262 of RVi/Shenyang. Liaoning. CHN/13.11/4 and RVi/Liaoyang. Liaoning. CHN/26. 11/2. there had no change found in the important antigenic epitope sites, the hemagglutination inhibition and neutralization epitopes of the other rubella viruses. All the 145 strains isolated had the same amino acid change (Leu338--Phe338) in E1 protein. These findings suggested that genotype 1E of rubella virus was the predominant genotype in Liaoning province. the rubella prevailed in recent six years was mainly caused by rubella viruses genotype 1E with multi-transmission routes.