컨텐츠 시작
학술대회/행사
초록검색
| 제출번호(No.) | 0246 |
|---|---|
| 분류(Section) | Poster Session |
| 분과(Session) | (AM) Applied Mathematics(including AI, Data Science) (AM) |
| 발표시간(Time) | 19th-B-14:00 -- 14:30 |
| 영문제목 (Title(Eng.)) |
An alternative approach for distinguishing immune reconstitution inflammatory syndrome (IRIS)-induced hepatic flare (HF) in HBV/HIV-1 co-infected patients |
| 저자(Author(s)) |
SooYoun Choi1, Hyeongki Park3, Kwang Su Kim2, Shingo Iwami3, Il Hyo Jung1 Pusan National University1, Pukyong National University2, Nagoya University3 |
| 초록본문(Abstract) | Immune reconstitution inflammatory syndrome (IRIS) occurs in approximately 20% of HBV/HIV-1 co-infected patients who initiate antiretroviral therapy (ART), due to dysregulated immune reconstitution leading to aberrant inflammation. When treating HBV/HIV-1 co-infected patients, it is difficult to determine whether the patient will experience IRIS, leading to confusion such as side effects or treatment discontinuation during the treatment process. HBV/HIV-1 co-infected patients under ART can experience IRIS-hepatic flare (IRIS-HF), characterized by a sudden increase in ALT levels of more than 5-fold or a decrease in HBsAg levels within 12 months of starting ART. The aim of this study is to identify characteristics that can be used for the diagnosis of IRIS by using the IRIS-HF phenomenon. We developed a multi-scale mathematical model that explicitly integrates intracellular and intercellular HBV infection processes, along with IRIS-HF arising from HBV/HIV-1 co-infected patients. Dynamics of biomarkers such as ALT, HBsAg, and HBV DNA in HBV/HIV-1 co-infected patients are quantitatively estimated through the model based on clinical data. Additionally, by using machine learning methods, we stratified HBV/HIV-1 co-infected patients and obtained unique features specific to IRIS-HF patients. Our approach could reduce the treatment burden for HBV/HIV-1 co-infected patients by addressing the limitations of existing methods for identifying IRIS. |
| 분류기호 (MSC number(s)) |
92-10 |
| 키워드(Keyword(s)) | Mathematical modeling, data analysis, HBV, HIV |
| 강연 형태 (Language of Session (Talk)) |
Korean |