Four-factor risk prediction method for clinically high-risk group of psychiatric patients

Abstract

The invention discloses a four-factor risk prediction method for a clinically high-risk group of psychiatric patients. By means of structured interview clinical data and MATRICS cognitive test batteryof prepsychotic symptoms, clinical data and cognitive data are quantified; between-group variance analysis is conducted according to whether or not an onset exists according to cohort's 2-year follow-up visit results, and14 variations with significant differences are selected; by means of principal component analysis in an exploratory factor analysis method, and by conducting factor-loaded orthogonal varimax rotation on the 14 variables, four coincidence factors are extracted; a regression model is built by means of four factors extracted through factor analysis, the built model is repeated through Bootstrap, and the stability of a prediction model is evaluated; 100 cases of a psychiatric high-risk cohort are collected and subjected to follow-up visit for two years, the validity of modelrisk prediction is verified. According to the risk degree accuracy worked out by the prediction model, application in Chinese population is significantly superior to the prior art, and the risk can besubjected to systematic analysis and precise control conveniently.

Description

technical field [0001] The invention belongs to the technical field of psychiatric diagnosis, and in particular relates to a four-factor risk prediction method for clinical high-risk groups of psychiatric diseases. Background technique [0002] Severe psychiatric disorders represented by schizophrenia are not only a clinical problem in psychiatry, but also one of the major problems in brain science research, but it is also related to the 16 million patient groups in China, people's livelihood, civil affairs, and social and family harmony. unavoidable problem. Existing treatment strategies often focus on dealing with the symptoms and functions after the onset of schizophrenia, with limited efficacy, making psychotic disorders a medical problem with low remission rate, high relapse rate, and high disability rate. In view of this, people of insight have pinned their hopes for treatment in the early or super early stage. This is a key transition from psychiatry to preventive me...

AI Technical Summary

Problems solved by technology

Secondly, for clinicians, it is not enough to only know the risk probability of psychosis in high-risk groups. In particular, the NAPLS-2 algorithm cannot obtain the factors that constitute the risk of onset, that is, they only know what they are without knowing why. If they can further obtain the risk factors that constitute the risk factors, the analysis of this risk will have more important value for clinical decision-making

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