Predicting the number of citations of polycystic kidney disease with 100 top-cited articles since 2010: Bibliometric analysis

This study aimed to predict the number of article citations using 100 top-cited PKD articles (T100PKDs) and dissect the characteristics of influential authors and affiliated counties since 2010. Methods: We searched the PubMed Central® (PMC) database and downloaded 100PKDs from 2010. Citation analysis was performed to compare the dominant countries and authors using social network analysis (SNA). MeSh terms were analyzed by referring to their citations in articles and used to predict the number of article citations using its correlation coefficients (CC) to examine the prediction effect. Results: We observed that the top 3 countries and journals in 100PKDs were the US (65%), Netherlands (7%), France (5%), J Am Soc Nephrol (21%), Clin J Am Soc Nephrol (8%), and N Engl J Med (6%); the most cited article (PMID = 23121377 with 473 citations) was authored by Vicente Torres from the US in 2012; and the most influential MeSH terms were drug therapy (3087.2), genetics (2997.83), and therapeutic use (2760.7). MeSH terms were evident in the prediction power of the number of article citations (CC = 0.37; t = 3.92; P 
Source: Medicine - Category: Internal Medicine Tags: Research Article: Systematic Review and Meta-Analysis Source Type: research