Nakamura Dan, Hanawa Yoichi, Seki Shizuka, Yamauchi Misato, Iwami Yuriko, Nagatsuka Yuta, Suzuki Hirohisa, Aoyagi Keisuke, Hayashi Wakaho, Otowa Takeshi, Iwanami Akira
Department of Psychiatry, Showa University School of Medicine, Tokyo, Japan.
Department of Psychiatry, Showa University Karasuyama Hospital, Tokyo, Japan.
Front Psychiatry. 2024 Dec 18;15:1493158. doi: 10.3389/fpsyt.2024.1493158. eCollection 2024.
Although schizophrenia and autism spectrum disorder (ASD) are currently conceptualized as distinct disorders, the similarity in their symptoms often makes differential diagnosis difficult. This study aimed to identify similarities and differences in the symptoms of schizophrenia and ASD to establish a more useful and objective differential diagnostic method and to identify ASD traits in participants with schizophrenia.
A total of 40 participants with schizophrenia (13 females, mean age: 34 ± 11 years) and 50 participants with ASD (15 females, mean age: 34 ± 8 years) were evaluated using the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) and other clinical measures.
ADOS-2 Module 4 original and revised algorithms did not significantly discriminate schizophrenia and ASD, whereas the "Predictive Model" combining the A7, A10, B1, B6, B8, and B9 showed superior accuracy in differentiating both disorders. Both algorithms in the ADOS-2 had high schizophrenia false-positive rates, and significant positive correlations were observed between all domains and the total scores of both algorithms in the ADOS-2 and Positive and Negative Syndrome Scale (PANSS) negative scale scores in the schizophrenia group. The PANSS negative-scale scores were significantly higher in patients positive for autism spectrum cut-offs (CutOff-POS) than in patients negative for autism spectrum cut-offs (CutOff-NEG) for both algorithms in the ADOS-2. Logistic regression analysis revealed that the positivity for both algorithm scales in the ADOS-2 was predicted using only the PANSS negative scale scores.
This study showed that a combination of several items in the ADOS-2 is useful for discriminating between ASD and schizophrenia. The study's findings could help develop strategies benefiting ASD and schizophrenia treatments.
尽管精神分裂症和自闭症谱系障碍(ASD)目前被概念化为不同的疾病,但它们症状的相似性常常使鉴别诊断变得困难。本研究旨在确定精神分裂症和ASD症状的异同,以建立一种更有用和客观的鉴别诊断方法,并识别精神分裂症患者中的ASD特征。
使用《自闭症诊断观察量表第二版》(ADOS-2)和其他临床测量方法对40名精神分裂症患者(13名女性,平均年龄:34±11岁)和50名ASD患者(15名女性,平均年龄:34±8岁)进行评估。
ADOS-2模块4的原始算法和修订算法未能显著区分精神分裂症和ASD,而结合A7、A10、B1、B6、B8和B9的“预测模型”在区分这两种疾病方面显示出更高的准确性。ADOS-2中的两种算法在精神分裂症方面的假阳性率都很高,并且在精神分裂症组中,ADOS-2的所有领域与总分以及阳性和阴性症状量表(PANSS)阴性量表得分之间均观察到显著的正相关。对于ADOS-2中的两种算法,自闭症谱系临界值为阳性(CutOff-POS)的患者的PANSS阴性量表得分显著高于自闭症谱系临界值为阴性(CutOff-NEG)的患者。逻辑回归分析表明,仅使用PANSS阴性量表得分就能预测ADOS-2中两种算法量表的阳性结果。
本研究表明,ADOS-2中几个项目的组合有助于区分ASD和精神分裂症。该研究结果有助于制定有利于ASD和精神分裂症治疗的策略。