서울대학교 생물정보학 협동과정 주최로 세미나를 아래와 같이 열고자 하오니 많은 참여 바랍니다.

세미나는 Zoom을 통한 온라인 강의로 예정되어 있으며 강의에 참여하고자 하시는 분께서는　 mari911@snu.ac.kr로 메일 주시면 강의 링크 전달드리도록 하겠습니다.　

일시:　　2020년 4월 14일　화요일 오전 11시

연사:　　백효정 연사님　(KISTI)

TITLE

Scalable research in KISTI: Tracing millions of patients for precision medicine

Abstract

The identification of novel disease associations using big-data for patient care has had limited success. In　this study, we created a longitudinal disease network of traced readmissions (disease trajectories), merging　data from over 10.4 million inpatients through the Healthcare Cost and Utilization Project, which allowed　the representation of disease progression mapping of over 300 diseases. From these disease trajectories, we　discovered an interesting association between schizophrenia and rhabdomyolysis, a rare muscle disease　(incidence <1E-04) (relative risk, 2.21 [1.80–2.71, confidence interval = 0.95] P-value 9.54E-15). We　validated this association by using independent electronic medical records from over 830,000 patients at the　University of California, San Francisco (UCSF) medical center. A case review of 29 rhabdomyolysis　incidents in schizophrenia patients at UCSF demonstrated that 62% are idiopathic, without the use of any　drug known to lead to this adverse event, suggesting a warning to physicians to watch for this unexpected　risk of schizophrenia. Large-scale analysis of disease trajectories can help physicians understand potential　sequential events in their patients.