Individualized prediction of psychiatric readmissions for patients with major depressive disorder: a 10-year retrospective cohort study.

ABSTRACT: Patients with major depressive disorder (MDD) are at high risk of psychiatric readmission while the factors associated with such adverse illness trajectories and the impact of the same factor at different follow-up times remain unclear. Based on machine learning (ML) approaches and real-world electronic medical records (EMR), we aimed to predict individual psychiatric readmission within 30, 60, 90, 180, and 365 days of an initial major depression hospitalization. In addition, we examined to what extent our prediction model could be made interpretable by quantifying and visualizing the features that drive the predictions at different follow-up times. By identifying 13,177 individuals discharged from a hospital located in western China between 2009 and 2018 with a recorded diagnosis of MDD,

SUBMITTER: Zhu T 

PROVIDER: S-EPMC9035153 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature