The prevalence of hyperuricemia in China: a meta-analysis

<p>Abstract</p> <p>Background</p> <p>The prevalence of hyperuricemia varied in different populations and it appeared to be increasing in the past decades. Recent studies suggest that hyperuricemia is an independent risk factor for cardiovascular disease. However, there has not yet been a systematic analysis of the prevalence of hyperuricemia in China.</p> <p>Methods</p> <p>Epidemiological investigations on hyperuricemia in China published in journals were identified manually and on-line by using CBMDISC, Chongqing VIP database and CNKI database. Those Reported in English journals were identified using MEDLINE database. Selected studies had to describe an original study defined by strict screening and diagnostic criteria. The fixed effects model or random effects model was employed according to statistical test for homogeneity.</p> <p>Results</p> <p>Fifty-nine studies were selected, the statistical information of which was collected for systematic analysis. The results showed that the pooled prevalence of hyperuricemia in male was 21.6% (95%CI: 18.9%-24.6%), but it was only 8.6% (95%CI: 8.2%-10.2%) in female. It was found that thirty years was the risk point age in male and it was fifty years in female.</p> <p>Conclusions</p> <p>The prevalence of hyperuricemia is different as the period of age and it increases after 30 years in male and 50 in female. Interventions are necessary to change the risk factors before the key age which is 30 years in male and 50 in female.</p

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research