识别维生素 D 研究的近期趋势：一种定量和共词分析。

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.

背景：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。

材料和方法：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。

结果：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。

结论：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。