AI-based prediction of depression symptomatology in first-episode psychosis patients: insights from the EUFEST and RAISE-ETP clinical trials.

ABSTRACT:

Background

Depressive symptoms are highly prevalent in first-episode psychosis (FEP) and worsen clinical outcomes. It is currently difficult to determine which patients will have persistent depressive symptoms based on a clinical assessment. We aimed to determine whether depressive symptoms and post-psychotic depressive episodes can be predicted from baseline clinical data, quality of life, and blood-based biomarkers, and to assess the geographical generalizability of these models.

Methods

Two FEP trials were analyzed: European First-Episode Schizophrenia Trial (EUFEST) (n = 498; 2002-2006) and Recovery After an Initial Schizophrenia Episode Early Treatment Program (RAISE-ETP) (n = 404; 2010-2012). Participants included those aged 15-40 years, meeting Diagnosti

SUBMITTER: Mena S 

PROVIDER: S-EPMC12341035 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature