BACKGROUND: Improving the identification of clinical vulnerability to psychosis in help-seeking subjects is crucial for refining risk stratifications and implementing intervention strategies. AIMS: To define underlying dimensions of subclinical psychopathology in Ultra-High-Risk (UHR) subjects; to test their temporal stability and association with baseline clinical and functional features; and to evaluate their predictive value for subsequent transition to psychosis. METHOD: 223 subjects meeting the Personal Assessment and Crisis Evaluation (PACE) criteria for UHR were assessed with the Comprehensive Assessment of At-Risk Mental States (CAARMS) and monitored for a period of up to three years. Data were analysed via principal component analysis (PCA), Spearman correlation analysis and Cox regression. RESULTS: PCA of the CAARMS yielded three orthogonal symptom clusters (negative, disorganized and perceptual-affective instability) with substantial temporal stability over a one-month time span. These clusters were strongly related to global functioning, quality of life, baseline major psychopathology and duration of symptoms before referral. The severity of the CAARMS disorganized component was the strongest predictor of transition to frank psychosis at follow-up. CONCLUSIONS: A dimensional approach to CAARMS-measured symptoms may refine current early identification heuristics and provide an alternative way to characterize UHR profiles complementary to the current categorical one.
BACKGROUND: Improving the identification of clinical vulnerability to psychosis in help-seeking subjects is crucial for refining risk stratifications and implementing intervention strategies. AIMS: To define underlying dimensions of subclinical psychopathology in Ultra-High-Risk (UHR) subjects; to test their temporal stability and association with baseline clinical and functional features; and to evaluate their predictive value for subsequent transition to psychosis. METHOD: 223 subjects meeting the Personal Assessment and Crisis Evaluation (PACE) criteria for UHR were assessed with the Comprehensive Assessment of At-Risk Mental States (CAARMS) and monitored for a period of up to three years. Data were analysed via principal component analysis (PCA), Spearman correlation analysis and Cox regression. RESULTS: PCA of the CAARMS yielded three orthogonal symptom clusters (negative, disorganized and perceptual-affective instability) with substantial temporal stability over a one-month time span. These clusters were strongly related to global functioning, quality of life, baseline major psychopathology and duration of symptoms before referral. The severity of the CAARMS disorganized component was the strongest predictor of transition to frank psychosis at follow-up. CONCLUSIONS: A dimensional approach to CAARMS-measured symptoms may refine current early identification heuristics and provide an alternative way to characterize UHR profiles complementary to the current categorical one.
Authors: Diana O Perkins; Clark D Jeffries; Barbara A Cornblatt; Scott W Woods; Jean Addington; Carrie E Bearden; Kristin S Cadenhead; Tyrone D Cannon; Robert Heinssen; Daniel H Mathalon; Larry J Seidman; Ming T Tsuang; Elaine F Walker; Thomas H McGlashan Journal: Schizophr Res Date: 2015-10-04 Impact factor: 4.939
Authors: Rebbekah J Atkinson; W Ross Fulham; Patricia T Michie; Philip B Ward; Juanita Todd; Helen Stain; Robyn Langdon; Renate Thienel; Georgie Paulik; Gavin Cooper; Ulrich Schall Journal: PLoS One Date: 2017-02-10 Impact factor: 3.240