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[A study of visual expression on ulinastatin usage].

Si-han Lin1, Si-yan Zhan

  • 1Department of Epidemiology and Bio-statistics, School of Public Health, Peking University, Beijing 100191, China. Corresponding author: Lin Si-han,

Zhonghua Wei Zhong Bing Ji Jiu Yi Xue
|January 23, 2014
PubMed
Summary
This summary is machine-generated.

Ulinastatin (urinary trypsin inhibitor) is used to treat hundreds of diseases across multiple ICD-10 categories. Analysis reveals a common therapeutic foundation for ulinastatin despite varied indications, visualized through data mapping.

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Area of Science:

  • Biomedical research
  • Pharmacology
  • Medical informatics

Background:

  • Ulinastatin, a urinary trypsin inhibitor, has diverse clinical applications.
  • Understanding the research landscape of ulinastatin is crucial for its effective clinical use.

Purpose of the Study:

  • To comprehensively analyze and visualize research on ulinastatin's clinical applications.
  • To identify common therapeutic mechanisms and disease associations for ulinastatin treatment.

Main Methods:

  • Systematic literature search of English and Chinese articles up to 2012/2013.
  • Keyword extraction for diseases and treatment mechanisms using Bibexcel.
  • Classification of diseases (ICD-10) and treatment mechanisms (immunity, coagulation, genetic/metabolic).
  • Multidimensional scaling (MDS) and word co-occurrence matrix analysis for visualizing relationships.

Main Results:

  • Analysis of 3,660 articles, covering 97 diseases (English) and 220 diseases (Chinese).
  • Identified 74 (English) and 33 (Chinese) treatment mechanism keywords, categorized into immunity/inflammation, coagulation, and genetic/metabolic.
  • MDS revealed common therapeutic foundations for ulinastatin across diverse diseases, despite varied indications.

Conclusions:

  • Ulinastatin treatment is extensively researched across hundreds of diseases and multiple ICD-10 categories.
  • A common therapeutic basis for ulinastatin exists, supported by word co-occurrence analysis.
  • Visual data representation successfully achieved the study's objective, offering insights for future research.