Models of mild cognitive deficits in risk assessment in early psychosis

作者：Tianhong Zhang, HuiRu Cui, XiaoChen Tang, Lihua Xu, YanYan Wei, YeGang Hu, Yingying Tang, Zixuan Wang, HaiChun Liu, Tao Chen, Chunbo Li, Jijun Wang · 发表于：Psychological Medicine · 年份：2024 · DOI：10.1017/s0033291724000382 · 被引用次数：10 · 研究领域：Schizophrenia research and treatment、Dementia and Cognitive Impairment Research、Cognitive Functions and Memory

Abstract Background Mild cognitive deficits (MCD) emerge before the first episode of psychosis (FEP) and persist in the clinical high-risk (CHR) stage. This study aims to refine risk prediction by developing MCD models optimized for specific early psychosis stages and target populations. Methods A comprehensive neuropsychological battery assessed 1059 individuals with FEP, 794 CHR, and 774 matched healthy controls (HCs). CHR subjects, followed up for 2 years, were categorized into converters (CHR-C) and non-converters (CHR-NC). The MATRICS Consensus Cognitive Battery standardized neurocognitive tests were employed. Results Both the CHR and FEP groups exhibited significantly poorer performance compared to the HC group across all neurocognitive tests (all p < 0.001). The CHR-C group demonstrated poorer performance compared to the CHR-NC group on three sub-tests: visuospatial memory ( p < 0.001), mazes ( p = 0.005), and symbol coding ( p = 0.023) tests. Upon adjusting for sex and age, the performance of the MCD model was excellent in differentiating FEP from HC, as evidenced by an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.895 ( p < 0.001). However, when applied in the CHR group for predicting CHR-C (AUC = 0.581, p = 0.008), the performance was not satisfactory. To optimize the efficiency of psychotic risk assessment, three distinct MCD models were developed to distinguish FEP from HC, predict CHR-C from CHR-NC, and identify CHR from HC, achieving...