Department of Nutrition, The First Hospital of China Medical University, Shenyang, Liaoning, China (mainland).
Department of Geriatric Endocrinology, The First Hospital of China Medical University, Shenyang, Liaoning, China (mainland).
Med Sci Monit. 2019 Jan 22;25:643-655. doi: 10.12659/MSM.913026.
BACKGROUND In recent years, many studies on vitamin D have been published. We combed these data for hot spot analyses and predicted future research topic trends. MATERIAL AND METHODS Articles (4625) concerning vitamin D published in the past 3 years were selected as a study sample. Bibliographic Items Co-occurrence Matrix Builder (BICOMB) software was used to screen high-frequency Medical Subject Headings (MeSH) terms and construct a MeSH terms-source article matrix and MeSH terms co-occurrence matrix. Then, Graphical Clustering Toolkit (gCLUTO) software was employed to analyze the matrix by double-clustering and visual analysis to detect the trends on the subject. RESULTS Ninety high-frequency major MeSH terms were obtained from 4625 articles and divided into 5 clusters, and we generated a visualized matrix and a mountain map. Strategic coordinates were established by the co-occurrence matrix of the MeSH terms based on the above classification, and the 5 clusters described above were further divided into 7 topics. We classified the vitamin D-related diseases into 12 categories and analyzed their distribution. CONCLUSIONS The analysis of strategic coordinates revealed that the epidemiological study of vitamin D deficiency and vitamin D-related diseases is a hot research topic. The use of vitamin D in the prevention and treatment of some diseases, especially diabetes, was found to have a significant potential future research value.
近年来，发表了许多关于维生素 D 的研究。我们对这些数据进行了梳理，以进行热点分析，并预测未来的研究主题趋势。
选择过去 3 年发表的有关维生素 D 的 4625 篇文章作为研究样本。使用 Bibliographic Items Co-occurrence Matrix Builder (BICOMB) 软件筛选高频医学主题词 (MeSH) 术语，并构建 MeSH 术语-来源文章矩阵和 MeSH 术语共现矩阵。然后，使用 Graphical Clustering Toolkit (gCLUTO) 软件通过双聚类和可视化分析对矩阵进行分析，以检测主题趋势。
从 4625 篇文章中获得了 90 个高频主要 MeSH 术语，分为 5 个簇，并生成了可视化矩阵和山脉图。基于上述分类，通过 MeSH 术语的共现矩阵建立了战略坐标，将上述 5 个簇进一步分为 7 个主题。我们将维生素 D 相关疾病分为 12 类，并分析了它们的分布。
战略坐标的分析表明，维生素 D 缺乏症和维生素 D 相关疾病的流行病学研究是一个热门研究课题。维生素 D 在预防和治疗某些疾病（特别是糖尿病）中的应用具有显著的未来研究价值。
