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Multivariable prediction of functional outcome after first-episode psychosis: a crossover validation approach in EUFEST and PSYSCAN
- Source :
- Schizophrenia, Vol 10, Iss 1, Pp 1-11 (2024)
- Publication Year :
- 2024
- Publisher :
- Nature Portfolio, 2024.
-
Abstract
- Abstract Several multivariate prognostic models have been published to predict outcomes in patients with first episode psychosis (FEP), but it remains unclear whether those predictions generalize to independent populations. Using a subset of demographic and clinical baseline predictors, we aimed to develop and externally validate different models predicting functional outcome after a FEP in the context of a schizophrenia-spectrum disorder (FES), based on a previously published cross-validation and machine learning pipeline. A crossover validation approach was adopted in two large, international cohorts (EUFEST, n = 338, and the PSYSCAN FES cohort, n = 226). Scores on the Global Assessment of Functioning scale (GAF) at 12 month follow-up were dichotomized to differentiate between poor (GAF current
- Subjects :
- Psychiatry
RC435-571
Subjects
Details
- Language :
- English
- ISSN :
- 27546993
- Volume :
- 10
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Schizophrenia
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.303631fe2e7a477d8b64db7b350e187d
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41537-024-00505-w