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Updated: Oct 14, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Cognitive Patterns and Conversion in a Representative Sample of Individuals at Risk for Psychosis
Natalia Mansur Haddad1, Lucas Hortêncio1, Julio Cesar Andrade1
1Laboratorio de Neurociencias (LIM 27), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo.
Abstract:
Clinical high-risk (CHR) individuals belong to a heterogeneous group, of which only a few will cross the threshold for a clinical diagnosis. Cognitive disturbances are present in CHR subjects and may be indicative of transition. Our study aims to identify such deficits in a representative CHR for psychosis sample. Our sample comprised 92 CHR individuals and 54 controls from a representative cohort of the general population. They were followed up for a mean of 2.5 years, with 15 individuals converting to schizophrenia or other Diagnostic and Statistical Manual of Mental Disorders, 5th Edition diagnoses. Neurocognitive assessment was performed with the University of Pennsylvania Computerized Neuropsychological Testing, and CHR status was assessed with the Structured Interview for Prodromal Syndromes (SIPS). Baseline scores were entered in a latent profile analysis model. Our study brought forward a four-class model on cognitive performance. One class displayed better performance, whereas the other three performed worse, all compared with controls. The class with lower executive function also had the highest score on disorganized communication (SIPS P5 = 1.36, p < 0.05), although unrelated to conversion. Among the low performers, the class significantly related to conversion (p = 0.023) had the highest score in decreased expression of emotion (SIPS N3 = 0.85, p < 0.05). Our study brings new and relevant data on non-help-seeking CHR individuals and the relationship between cognitive patterns and conversion. We have highlighted a specific cognitive signature, associated with negative symptoms, which represents a stable trait with presumed lower conversion to a psychiatric illness.
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