Visualized Subject Knowledge-Mapping Study in Current Status of Diagnosis and Therapy for Kawasaki Disease Based on Multiple Statistical and Social Network Analysis

Abstract

Objective Study the subject domain knowledge of and therapy of Kawasaki in our country using multiple statistical and social network analysis, and finally built visualized knowledge-mapping. Methods The China Biology Medicine disc (CBM) (from January 1978 to December 2010) searched using medical subject headings (MESH) key word mucocutaneous lymph node syndrome, and imported the enrolled articles into Endnote X4. After key words had been characterized by Endnote X4, the co-occurrence matrix was built. Transformation, dimensionality reduction and clustering of co-occurrence matrix were finished by SPSS 17. 0,leading the strategic plot to be built. Then visualized networks were drawn in Ucinet 6. 0. Results A total of 3 603 articles were enrolled in this search. The visualized domain knowledge-mapping was successfully built, and it directly reflected the structure of knowledge-mapping of the subject. And key clusters were formed,in which the therapy and medicine application cluster had developed well. Injuries of coronary and cardiological examination and the diagnosis and clinical clusters developed unbalanced. While as the procedure and mechanism of Kawasaki disease cluster was in far below developed. Conclusions Therapy and medicine application,diagnosis and of coronary arteries of Kawasaki are well developed,stand in the center of the subject domain knowledge-mapping, and follow with several clusters. The study of characteristics and the cutting-edge therapy projects make great contribution to the progress of the subject. The studies of coronary artery injuries and clinical signs play an important role in the structure of the knowledge-mapping. Further researches in pathogenesis of Kawasaki need to be enhanced. Key words: multiple statistical analysis; social network analysis; Kawasaki disease; knowledge-mapping; visualized study