利用桑基图对 2013 年以来关于化脓性汗腺炎主题的 100 篇高被引论文进行引文分析：文献计量分析。

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic, inflammatory and debilitating dermatosis characterized by painful nodules, sinus tracts and abscesses in apocrine gland-bearing areas that predominantly affect women worldwide. New therapeutic interventions based on the clinical manifestations of patients have recently been introduced in numerous articles. However, which countries, journals, subject categories, and articles have the ultimate influence remain unknown. This study aimed to display influential entities in 100 top-cited HS-related articles (T100HS) and investigate whether medical subject headings (i.e., MeSH terms) can be used to predict article citations. METHODS: T100HS data were extracted from PubMed since 2013. Subject categories were classified by MeSH terms using social network analysis. Sankey diagrams were applied to highlight the top 10 influential entities in T100HS from the three aspects of publication, citations, and the composited score using the hT index. The difference in article citations across subject categories and the predictive power of MeSH terms on article citations in T100HS were examined using one-way analysis of variance and regression analysis. RESULTS: The top three countries (the US, Italy, and Spain) accounts for 54% of the T100HS. The T100HS impact factor (IF) is 12.49 (IF = citations/100). Most articles were published in J Am Acad Dermatol (15%; IF = 18.07). Eight subject categories were used. The "methods" was the most frequent MeSH term, followed by "surgery" and "therapeutic use". Saunte et al, from Roskilde Hospital, Denmark, had 149 citations in PubMed for the most cited articles. Sankey diagrams were used to depict the network characteristics of the T100HS. Article citations did not differ by subject category (F(7, 92) = 1.97, P = .067). MeSH terms were evident in the number of article citations predicted (F(1, 98) = 129.1106; P < .001). CONCLUSION: We achieved a breakthrough by displaying the characteristics of the T100HS network on the Sankey diagrams. MeSH terms may be used to classify articles into subject categories and predict T100HS citations. Future studies can apply the Sankey diagram to the bibliometrics of the 100 most-cited articles.

背景：化脓性汗腺炎（HS）是一种慢性、炎症性和使人虚弱的皮肤病，其特征为在大汗腺分布区域出现疼痛性结节、窦道和脓肿，主要影响全球女性。最近，许多文章中介绍了基于患者临床表现的新治疗干预措施。然而，哪些国家、期刊、主题类别和文章具有最终影响力仍不清楚。本研究旨在展示 100 篇高引化脓性汗腺炎相关文章（T100HS）中的有影响力的实体，并探讨医学主题词（即 MeSH 术语）是否可用于预测文章引用量。

方法：自 2013 年以来，从 PubMed 中提取 T100HS 数据。使用社会网络分析方法，根据 MeSH 术语对主题类别进行分类。使用 hT 指数的 Sankey 图突出显示 T100HS 中来自出版、引文和综合得分三个方面的前 10 个有影响力的实体。使用单向方差分析和回归分析检验了主题类别之间文章引用量的差异以及 MeSH 术语对 T100HS 中文章引用量的预测能力。

结果：排名前三的国家（美国、意大利和西班牙）占 T100HS 的 54%。T100HS 的影响因子（IF）为 12.49（IF=引文数/100）。大多数文章发表在《美国皮肤病学会杂志》（15%；IF=18.07）。使用了 8 个主题类别。最常见的 MeSH 术语是“方法”，其次是“手术”和“治疗用途”。丹麦罗斯基勒医院的 Saunte 等人在 PubMed 上发表的文章被引频次最高，达 149 次。Sankey 图用于描绘 T100HS 的网络特征。文章引用量不因主题类别而异（F(7, 92)=1.97，P=0.067）。MeSH 术语可用于预测文章引用量（F(1, 98)=129.1106；P<.001）。

结论：我们通过在 Sankey 图上展示 T100HS 网络的特征取得了突破。MeSH 术语可用于将文章分类到主题类别中并预测 T100HS 引文。未来的研究可以将 Sankey 图应用于 100 篇高引文章的文献计量学分析。