Suppr超能文献

自闭症的诊断:来自自闭症诊断访谈的数据的分析

Diagnosing autism: analyses of data from the Autism Diagnostic Interview.

作者信息

Lord C, Pickles A, McLennan J, Rutter M, Bregman J, Folstein S, Fombonne E, Leboyer M, Minshew N

机构信息

Department of Psychiatry, University of Chicago, Illinois 60637, USA.

出版信息

J Autism Dev Disord. 1997 Oct;27(5):501-17. doi: 10.1023/a:1025873925661.

Abstract

Results from ROC curves of items from two scales, the Autism Diagnostic Interview (ADI) and Autism Diagnostic Interview-Revised (ADI-R), operationalizing DSM-IV criteria for autism are presented for 319 autistic and 113 other subjects from 8 international autism centers. Analyses indicate that multiple items were necessary to attain adequate sensitivity and specificity if samples with varying levels of language were considered separately. Although considering only current behavior was generally sufficient when a combination cutoff and additive model was employed, predictive power was highest when history was taken into account. A single set of criteria, as operationalized by individually structured questions in the ADI/ADI-R, was effective in differentiating autism from mental handicap and language impairment in subjects with a range of chronological ages and developmental levels.

摘要

来自8个国际自闭症中心的319名自闭症患者和113名其他受试者的研究结果显示,用于实施《精神疾病诊断与统计手册》第四版(DSM-IV)自闭症标准的两个量表——《自闭症诊断访谈》(ADI)和《自闭症诊断访谈修订版》(ADI-R)——各项目的ROC曲线。分析表明,如果分别考虑语言水平不同的样本,需要多个项目才能获得足够的敏感性和特异性。虽然在采用组合临界值和累加模型时,仅考虑当前行为通常就足够了,但考虑病史时预测能力最高。ADI/ADI-R中通过单独构建的问题实施的单一标准集,能够有效地区分不同年龄和发育水平的自闭症患者与智力障碍和语言障碍患者。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验