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Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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Early Detection of Psychosis: Recent Updates from Clinical High-Risk Research
Ariel Schvarcz1, Carrie E Bearden2
1Department of Psychology, University of California, Los Angeles.
Abstract:
The debilitating nature of schizophrenia necessitates early detection of individuals at clinical high-risk (CHR) in order to facilitate early intervention. In particular, comparisons between those who develop fully psychotic features (CHR+) and those who do not (CHR-) offer the opportunity to reveal distinct risk factors for psychosis, as well as possible intervention target points. Recent studies have investigated baseline clinical, neurocognitive, neuroanatomic, neurohormonal, and psychophysiological predictors of outcome; premorbid social dysfunction, deficits in neurocognitive performance, neuroanatomic changes, and hypothalamic-pituitary-adrenal (HPA) axis dysfunction have been implicated in psychosis emergence. However, several challenges within CHR research remain: heterogeneity in long-term diagnostic outcome, the variability of research tools and definitions utilized, and limited longitudinal follow-up. Future work in the field should focus on replication via extended longitudinal designs, aim to explore the trajectories and inter-relationships of hypothesized biomarkers, and continue to investigate interventions that seek to prevent psychosis emergence through symptom reduction.
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