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Antipsychotics are widely used for treating patients with psychosis, and target threshold psychotic symptoms. Individuals at clinical high risk (CHR) for psychosis are characterized by subthreshold psychotic symptoms. It is currently unclear who might benefit from antipsychotic treatment. Our objective was to apply a risk calculator (RC) to identify people that would benefit from antipsychotics.
Drawing on 400 CHR individuals recruited between 2011 and 2016, 208 individuals who received antipsychotic treatment were included. Clinical and cognitive variables were entered into an individualized RC for psychosis; personal risk was estimated and 4 risk components (negative symptoms-RC-NS, general function-RC-GF, cognitive performance-RC-CP, and positive symptoms-RC-PS) were constructed. The sample was further stratified according to the risk level. Higher risk was defined based on the estimated risk score (20% or higher).
In total, 208 CHR individuals received daily antipsychotic treatment of an olanzapine-equivalent dose of 8.7 mg with a mean administration duration of 58.4 weeks. Of these, 39 (18.8%) developed psychosis within 2 years. A new index of factors ratio (FR), which was derived from the ratio of RC-PS plus RC-GF to RC-NS plus RC-CP, was generated. In the higher-risk group, as FR increased, the conversion rate decreased. A small group (15%) of CHR individuals at higher-risk and an FR >1 benefitted from the antipsychotic treatment.
Through applying a personal risk assessment, the administration of antipsychotics should be limited to CHR individuals with predominantly positive symptoms and related function decline. A strict antipsychotic prescription strategy should be introduced to reduce inappropriate use.
Only 30% or fewer of individuals at clinical high risk (CHR) convert to full psychosis within 2 years. Efforts are thus underway to refine risk identification strategies to increase their predictive power. Our objective was to develop and validate the predictive accuracy and individualized risk components of a mobile app-based psychosis risk calculator (RC) in a CHR sample from the SHARP (ShangHai At Risk for Psychosis) program.
In total, 400 CHR individuals were identified by the Chinese version of the Structured Interview for Prodromal Syndromes. In the first phase of 300 CHR individuals, 196 subjects (65.3%) who completed neurocognitive assessments and had at least a 2-year follow-up assessment were included in the construction of an RC for psychosis. In the second phase of the SHARP sample of 100 subjects, 93 with data integrity were included to validate the performance of the SHARP-RC.
The SHARP-RC showed good discrimination of subsequent transition to psychosis with an AUC of 0.78 (p < 0.001). The individualized risk generated by the SHARP-RC provided a solid estimation of conversion in the independent validation sample, with an AUC of 0.80 (p = 0.003). A risk estimate of 20% or higher had excellent sensitivity (84%) and moderate specificity (63%) for the prediction of psychosis. The relative contribution of individual risk components can be simultaneously generated. The mobile app-based SHARP-RC was developed as a convenient tool for individualized psychosis risk appraisal.
The SHARP-RC provides a practical tool not only for assessing the probability that an individual at CHR will develop full psychosis, but also personal risk components that might be targeted in early intervention.
Event-related potentials (ERPs) provide a noninvasive
method to evaluate neural activation and cognitive processes
in schizophrenia. The pathophysiological significance of
these findings would be greatly enhanced if scalp-recorded
ERP abnormalities could be related to specific neural circuits
and/or regions of the brain. Using quantitative approaches
in which scalp-recorded ERP components are correlated with
underlying neuroanatomy in schizophrenia, we focused on
biophysical and statistical procedures (partial least squares)
to relate the auditory P300 component to anatomic measures
obtained from quantitative magnetic resonance imaging.
These findings are consistent with other evidence that
temporal lobe structures contribute to the generation of
the scalp-recorded P300 component and that P300 amplitude
asymmetry over temporal recording sites on the scalp may
reflect anatomic asymmetries in the volume of the superior
temporal gyrus in schizophrenia.
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