Department of Psychiatry, Sawai Man Singh Medical College, Jaipur, India.
InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru 560029, India.
Psychiatry Res. 2022 Oct;316:114731. doi: 10.1016/j.psychres.2022.114731. Epub 2022 Jul 17.
Cognitive deficit is one of the core features of schizophrenia and is associated with poor functional outcomes. There is a lack of validated criteria to screen and monitor cognitive deficits in schizophrenia. This study aimed to evaluate the concurrent validity and sensitivity of MoCA (Montreal Cognitive Assessment) and DSST (Digit Symbol Substitution Test) in identifying cognitive deficits in Schizophrenia comparing with a comprehensive MCCB [MATRICS (Measurement And Treatment Research to Improve Cognition in Schizophrenia) Consensus Cognitive Battery] equivalent battery. We did clinical and cognitive assessments on 30 patients with schizophrenia and 30 age and gender-matched healthy controls. The Cronbach's Alpha of MoCA was 0.839, and on adding the DSST, it increased to 0.859. In stepwise binary logistic regression, adding DSST to MoCA improved the prediction of cognitive impairment as defined by a comprehensive battery with 86.7% classification accuracy. Receiver operating characteristic curve analysis suggested a score of 25 of MoCA and 59 of DSST as an optimal cut-off in identifying severe cognitive deficits with an additional MoCA cut-off of 27 for identifying mild cognitive deficits. Combined MoCA and DSST is a sensitive and quick method to screen for neurocognitive deficits in schizophrenia.
认知缺陷是精神分裂症的核心特征之一,与较差的功能结果相关。目前缺乏有效的标准来筛选和监测精神分裂症患者的认知缺陷。本研究旨在评估 MoCA(蒙特利尔认知评估)和 DSST(数字符号替代测试)在识别精神分裂症认知缺陷方面的同时效度和敏感性,将其与等效的 MCCB [MATRICS(用于改善精神分裂症认知的测量和治疗研究共识认知电池)]进行比较。我们对 30 名精神分裂症患者和 30 名年龄和性别匹配的健康对照者进行了临床和认知评估。MoCA 的克朗巴赫 α系数为 0.839,加入 DSST 后增加到 0.859。在逐步二元逻辑回归中,将 DSST 添加到 MoCA 中可提高对认知障碍的预测,该认知障碍是通过综合电池定义的,分类准确率为 86.7%。受试者工作特征曲线分析表明,MoCA 得分为 25 分,DSST 得分为 59 分是识别严重认知缺陷的最佳截断值,MoCA 得分为 27 分是识别轻度认知缺陷的附加截断值。联合 MoCA 和 DSST 是一种敏感且快速的方法,可用于筛查精神分裂症的神经认知缺陷。