The new network PLP study is launched to validate machine learning model predicting newly diagnosed MDD patients within 1 year after initiation of beta-blocker for cardiovascular disease. The algorithm was developed on the Korean National Health Insurance Service - National Sample Cohort.
Background: Incident depression has been reported to be associated with poor prognosis in patients with cardiovascular disease (CVD), which might be caused by beta-blocker therapy. Since early detection and intervention for depression can alleviate the risk of future CVD risks in these patients, prediction model to identify high-risk patients for subsequent MDD may lead better outcome in patients requiring beta-blocker therapy.
The validation package is available at OhdsiStudy repo.
Since we’re aiming to submit the paper to the Special Issue of Journal of Personalized Medicine (Deadline: 20 December 2020), please let us know as soon as possible if you want to participate.
And please provide any comments or suggestions.