Applying machine learning to identify and characterize multimorbidity profiles with increased cardiovascular, cerebrovascular, and all-cause mortality risks in a retrospective cohort of antipsychotic users
Grant Data
Project Title
Applying machine learning to identify and characterize multimorbidity profiles with increased cardiovascular, cerebrovascular, and all-cause mortality risks in a retrospective cohort of antipsychotic users
Principal Investigator
Professor Lai, Tsz Tsun Francisco
(Principal Investigator (PI))
Co-Investigator(s)
Professor Tsoi Kam Fai, Kevin
(Co-Investigator)
Professor Wong Ian Chi Kei
(Co-Investigator)
Professor Chan Esther Wai Yin
(Co-Investigator)
Professor Chan Kit Wa
(Co-Investigator)
Duration
24
Start Date
2022-11-01
Amount
802608
Conference Title
Applying machine learning to identify and characterize multimorbidity profiles with increased cardiovascular, cerebrovascular, and all-cause mortality risks in a retrospective cohort of antipsychotic users
Keywords
Antipsychotics, Cardiovascular disease, Cerebrovascular disease, Drug safety, Machine learning
Discipline
Pharmacology/Toxicology
HKU Project Code
19201271
Grant Type
Health and Medical Research Fund - Full Grant
Funding Year
2022
Status
On-going
Objectives
In the context of multimorbidity, existing evidence is lacking on the potentially differing risk profiles of antipsychotics in relation to elevated cardiovascular and cerebrovascular mortality. We aim to 1. describe multimorbidity prevalence trends among Hong Kong antipsychotic users, 2. identify disease combinations as potential mortality risk classifiers and 3. use machine learning to predict mortality.