[show abstract][hide abstract] ABSTRACT: BACKGROUND: Fibrates has been extensively used to improve plasma lipid levels and prevent adverse cardiovascular outcomes. However, the effect of fibrates on stroke is unclear at the present time. We therefore carried out a comprehensive systematic review and meta-analysis to evaluate the effects of fibrates on stroke. METHODS: We systematically searched Medline, Embase, the Cochrane Central Register of Controlled Trials, reference lists of articles, and proceedings of major meetings to identify studies for our analysis. We included randomized placebo controlled trials which reported the effects of fibrates on stroke. Relative risk (RR) was used to measure the effect of fibrates on the risk of stroke under random effect model. The analysis was further stratified by factors that could affect the treatment effects. RESULTS: Overall, fibrate therapy was not associated with a significant reduction on the risk of stroke (RR, 1.02, 95%CI, 0.90 to 1.16, P = 0.78). In the subgroup analyses, we observed that gemfibrozil therapy showed a beneficial effect on stroke (RR, 0.72, 95%CI, 0.53 to 0.98, P = 0.04). Similarly, fibrate therapy comparing to placebo had no effect on the incidence of fatal stroke. Subgroup analysis suggested that fibrate therapy showed an effect on fatal stroke when the Jadad score more than 3 (RR, 0.41, 95%CI, 0.17 to 1.00, P = 0.049). Furthermore, a sensitivity analysis indicated that fibrate therapy may play a role in fatal stroke (RR, 0.49, 95%CI, 0.26 to 0.93, P = 0.03) for patients with previous diabetes, cardiovascular disease or stroke. CONCLUSIONS: Our study indicated that fibrate therapy might play an important role in reducing the risk of fatal stroke in patients with previous diabetes, cardiovascular disease or stroke. However, it did not have an effect on the incidence of stroke.
[show abstract][hide abstract] ABSTRACT: High quality clinical research not only requires advanced professional knowledge, but also needs sound study design and correct statistical analyses. The number of clinical research articles published in Chinese medical journals has increased immensely in the past decade, but study design quality and statistical analyses have remained suboptimal. The aim of this investigation was to gather evidence on the quality of study design and statistical analyses in clinical researches conducted in China for the first decade of the new millennium.
Ten (10) leading Chinese medical journals were selected and all original articles published in 1998 (N = 1,335) and 2008 (N = 1,578) were thoroughly categorized and reviewed. A well-defined and validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation. Main outcomes were the frequencies of different types of study design, error/defect proportion in design and statistical analyses, and implementation of CONSORT in randomized clinical trials. From 1998 to 2008: The error/defect proportion in statistical analyses decreased significantly ( = 12.03, p<0.001), 59.8% (545/1,335) in 1998 compared to 52.2% (664/1,578) in 2008. The overall error/defect proportion of study design also decreased ( = 21.22, p<0.001), 50.9% (680/1,335) compared to 42.40% (669/1,578). In 2008, design with randomized clinical trials remained low in single digit (3.8%, 60/1,578) with two-third showed poor results reporting (defects in 44 papers, 73.3%). Nearly half of the published studies were retrospective in nature, 49.3% (658/1,335) in 1998 compared to 48.2% (761/1,578) in 2008. Decreases in defect proportions were observed in both results presentation ( = 93.26, p<0.001), 92.7% (945/1,019) compared to 78.2% (1023/1,309) and interpretation ( = 27.26, p<0.001), 9.7% (99/1,019) compared to 4.3% (56/1,309), some serious ones persisted.
Chinese medical research seems to have made significant progress regarding statistical analyses, but there remains ample room for improvement regarding study designs. Retrospective clinical studies are the most often used design, whereas randomized clinical trials are rare and often show methodological weaknesses. Urgent implementation of the CONSORT statement is imperative.
PLoS ONE 01/2010; 5(5):e10822. · 3.73 Impact Factor
[show abstract][hide abstract] ABSTRACT: Nuclear receptors are involved in multiple cellular signaling pathways that affect and regulate processes. Because of their physiology and pathophysiology significance, classification of nuclear receptors is essential for the proper understanding of their functions. Bhasin and Raghava have shown that the subfamilies of nuclear receptors are closely correlated with their amino acid composition and dipeptide composition . They characterized each protein by a 400 dimensional feature vector. However, using high dimensional feature vectors for characterization of protein sequences will increase the computational cost as well as the risk of overfitting. Therefore, using only those features that are most relevant to the present task might improve the prediction system, and might also provide us with some biologically useful knowledge. In this paper a feature selection approach was proposed to identify relevant features and a prediction engine of support vector machines was developed to estimate the prediction accuracy of classification using the selected features. A reduced subset containing 30 features was accepted to characterize the protein sequences in view of its good discriminative power towards the classes, in which 18 are of amino acid composition and 12 are of dipeptide composition. This reduced feature subset resulted in an overall accuracy of 98.9% in a 5-fold cross-validation test, higher than 88.7% of amino acid composition based method and almost as high as 99.3% of dipeptide composition based method. Moreover, an overall accuracy of 93.7% was reached when it was evaluated on a blind data set of 63 nuclear receptors. On the other hand, an overall accuracy of 96.1% and 95.2% based on the reduced 12 dipeptide compositions was observed simultaneously in the 5-fold cross-validation test and the blind data set test, respectively. These results demonstrate the effectiveness of the present method.
Protein and Peptide Letters 02/2009; 16(7):823-9. · 1.99 Impact Factor
[show abstract][hide abstract] ABSTRACT: In this paper, a new data management system named EZ-Entry is introduced. Five major functions are enclosed in this system: (1) user authentication; (2) database construction; (3) double data entry with instant alignment; (4) revision tracking; (5) query management. The practical application performed on two clinical trials indicates that EZ-Entry meets the requirements of clinical data management with high efficiency and security. This software is freely available on request from the authors for academic purposes.
Computers in Biology and Medicine 10/2008; 38(9):1042-4. · 1.16 Impact Factor
[show abstract][hide abstract] ABSTRACT: G-protein coupled receptors (GPCRs) are involved in various physiological processes. Therefore, classification of amine type GPCRs is important for proper understanding of their functions. Though some effective methods have been developed, it still remains unknown how many and which features are essential for this task. Empirical studies show that feature selection might address this problem and provide us with some biologically useful knowledge. In this paper, a feature selection technique is introduced to identify those relevant features of proteins which are potentially important for the prediction of amine type GPCRs. The selected features are finally accepted to characterize proteins in a more compact form. High prediction accuracy is observed on two data sets with different sequence similarity by 5-fold cross-validation test. The comparison with a previous method demonstrates the efficiency and effectiveness of the proposed method.
Protein and Peptide Letters 02/2008; 15(8):834-42. · 1.99 Impact Factor