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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Establishment of Kawasaki disease database based on metadata standard
Yu Rang Park1, Jae-Jung Kim2, Young Jo Yoon3
1Clinical Research Center, Asan Institute of Life Sciences, Asan Medical Center, Seoul, Korea Department of Biomedical Informatics, Asan Medical Center, Seoul, Korea.
Abstract:
Kawasaki disease (KD) is a rare disease that occurs predominantly in infants and young children. To identify KD susceptibility genes and to develop a diagnostic test, a specific therapy, or prevention method, collecting KD patients' clinical and genomic data is one of the major issues. For this purpose, Kawasaki Disease Database (KDD) was developed based on the efforts of Korean Kawasaki Disease Genetics Consortium (KKDGC). KDD is a collection of 1292 clinical data and genomic samples of 1283 patients from 13 KKDGC-participating hospitals. Each sample contains the relevant clinical data, genomic DNA and plasma samples isolated from patients' blood, omics data and KD-associated genotype data. Clinical data was collected and saved using the common data elements based on the ISO/IEC 11179 metadata standard. Two genome-wide association study data of total 482 samples and whole exome sequencing data of 12 samples were also collected. In addition, KDD includes the rare cases of KD (16 cases with family history, 46 cases with recurrence, 119 cases with intravenous immunoglobulin non-responsiveness, and 52 cases with coronary artery aneurysm). As the first public database for KD, KDD can significantly facilitate KD studies. All data in KDD can be searchable and downloadable. KDD was implemented in PHP, MySQL and Apache, with all major browsers supported.Database URL: http://www.kawasakidisease.kr.
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