Schizophrenia ResearchNeurosciencePeer-reviewed journal article
Longitudinal Trajectory of Early Functional Recovery in Patients with First Episode Psychosis
Mei‐Hua HalliD, Kristina M. HoltoniD, Döst ÖngüriD, Debra M. Montrose, Matcheri S. KeshavaniD
Abstract
BackgroundThere is a large variability in the recovery trajectory and outcome of first episode of psychosis [FEP] patients. To date, individuals outcome trajectories at early stage of illness and potential risk factors associated with a poor outcome trajectory are largely unknown. This study aims to apply three separate predictors (positive symptoms, negative symptoms, and soft neurological signs) to identify homogeneous function outcome trajectories in patients with FEP using objective data-driven methods, and to explore the potential risk /protective factors associated with each trajectory.\n\nMethodsA total of 369 first episode patients (93% antipsychotic naive) were included in the baseline assessments and followed-up at 4-8 weeks, 6 months, and 1 year. K means cluster modelling for longitudinal data (kml3d) was used to identify distinct, homogeneous clusters of functional outcome trajectories. Patients with at least 3 assessments were included in the trajectory analyses (N=129). The Scale for the Assessment of Negative Symptoms (SANS), Scale for the Assessment of Positive Symptoms (SAPS), and Neurological examination abnormalities (NEA) were used as predictors against Global Assessment of Functioning Scale (GAF).\n\nResultsIn each of the three predictor models, four distinct functional outcome trajectories emerged: \"Poor\", \"Intermediate\", \"Good\" and \"Catch-up\". Individuals with male gender; ethnic minority status; low premorbid adjustment; low executive function/IQ, low SES, personality disorder, substance use history may be risk factors for poor recovery.\n\nConclusionsFunctioning recovery in individuals with FEP is heterogeneous, although distinct recovery profiles are apparent. Data-driven trajectory analysis can facilitate better characterization of individual longitudinal patterns of functioning recovery.
- Citations
- 80
- FWCI
- 7.15
- Field percentile
- top 2%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Predicting One-Year Outcome in First Episode Psychosis using Machine Learning
Samuel Leighton, Rajeev Krishnadas, … Andrew Ian Gumley·PLoS ONEPeer-reviewed·Mar 7, 2019
- Brain network connectivity underlying remission in early psychosis: a whole brain model approach
Ludovica Mana, Ane López‐González, … Gustavo Deco·Nature Mental HealthPeer-reviewed·Mar 27, 2025
- Longitudinal White Matter Trajectories in Clinical High Risk and First-Episode Psychosis: Findings from the Multi-Centre PSYSCAN Study
Lara Bolte, George Gifford, … Philip K. McGuire·bioRxiv·Jul 22, 2026
- Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated with Psychopathology Across Independent Cohorts
Haley R Wang, Zhen-Qi Liu, … Katherine H. Karlsgodt·Biological PsychiatryPeer-reviewed·Jun 20, 2024
- Abnormal reward prediction error signalling in antipsychotic naive individuals with first episode psychosis or clinical risk for psychosis
Anna O. Ermakova, Franziska Knolle, … Graham K. Murray·NeuropsychopharmacologyPeer-reviewed·Apr 5, 2018
- Neuroimaging alterations and relapse in early-stage psychosis
Marina M. Mihaljevic, Anisha Nagpal, … Akira Sawa·Journal of Psychiatry and NeurosciencePeer-reviewed·Apr 3, 2024