B-34 Correspondence of Latent Neurophysiological and Neurocognitive Profiles to Psychosis Biotypes

Autor: Milena Y Gotra, Tasha Rhoads, Scot Hill, Erin T Kaseda
Rok vydání: 2019
Předmět:
Zdroj: Archives of Clinical Neuropsychology. 34:980-980
ISSN: 1873-5843
DOI: 10.1093/arclin/acz034.117
Popis: Objective The Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) Consortium has developed a novel classification system for psychotic-spectrum disorders that emphasizes objective and neurobiologically valid measures. However, these ‘biotypes’ were created based on a lengthy battery of tests including electroencephalography (EEG), which is time-consuming to administer and not widely available in most clinical settings. The aim of the present study was to evaluate the degree to which classifications obtained using only cognitive and eye tracking paradigms correspond with the biotypes, which would allow for a more efficient approach to diagnosis of psychotic-spectrum disorders that could feasibly be implemented in a clinical setting. Method This study utilized latent profile analysis to identify distinct profiles in 683 patients diagnosed with schizophrenia, schizoaffective, or bipolar with psychosis and compared the solution to previously assigned biotypes. Results A 3-profile solution provided the best fit for the data (p = .02) and the profiles were characterized by varying degrees of cognitive and sensorimotor impairment. The most impaired profile accurately classified 58.1% of the probands in the most impaired biotype; the least impaired profile classified 63.4% of the least impaired biotype. The intermediate profile did not discriminate between biotypes. Conclusions Using composite scores to represent general cognition, eye tracking, and inhibitory control led to better classification of individuals at neurocognitive extremes, but not intermediate levels. These results suggest that the EEG findings are essential to better classify psychosis probands with intermediate impairment and contribute unique variance that may be clinically significant in classifying a subset of psychotic patients in treatment settings.
Databáze: OpenAIRE