Helgadóttir Halla, Gudmundsson Ólafur Ó, Baldursson Gísli, Magnússon Páll, Blin Nicolas, Brynjólfsdóttir Berglind, Emilsdóttir Ásdís, Gudmundsdóttir Gudrún B, Lorange Málfrídur, Newman Paula K, Jóhannesson Gísli H, Johnsen Kristinn
Mentis Cura, Reykjavik, Iceland.
Department of Child and Adolescent Psychiatry, Landspitali University Hospital, Reykjavik, Iceland.
BMJ Open. 2015 Jan 16;5(1):e005500. doi: 10.1136/bmjopen-2014-005500.
The aim of this study was to develop and test, for the first time, a multivariate diagnostic classifier of attention deficit hyperactivity disorder (ADHD) based on EEG coherence measures and chronological age.
The participants were recruited in two specialised centres and three schools in Reykjavik.
The data are from a large cross-sectional cohort of 310 patients with ADHD and 351 controls, covering an age range from 5.8 to 14 years. ADHD was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders fourth edition (DSM-IV) criteria using the K-SADS-PL semistructured interview. Participants in the control group were reported to be free of any mental or developmental disorders by their parents and had a score of less than 1.5 SDs above the age-appropriate norm on the ADHD Rating Scale-IV. Other than moderate or severe intellectual disability, no additional exclusion criteria were applied in order that the cohort reflected the typical cross section of patients with ADHD.
Diagnostic classifiers were developed using statistical pattern recognition for the entire age range and for specific age ranges and were tested using cross-validation and by application to a separate cohort of recordings not used in the development process. The age-specific classification approach was more accurate (76% accuracy in the independent test cohort; 81% cross-validation accuracy) than the age-independent version (76%; 73%). Chronological age was found to be an important classification feature.
The novel application of EEG-based classification methods presented here can offer significant benefit to the clinician by improving both the accuracy of initial diagnosis and ongoing monitoring of children and adolescents with ADHD. The most accurate possible diagnosis at a single point in time can be obtained by the age-specific classifiers, but the age-independent classifiers are also useful as they enable longitudinal monitoring of brain function.
本研究旨在首次开发并测试一种基于脑电图相干测量和实足年龄的注意力缺陷多动障碍（ADHD）多变量诊断分类器。
参与者招募自雷克雅未克的两个专业中心和三所学校。
数据来自一个大型横断面队列，包括310名ADHD患者和351名对照，年龄范围为5.8至14岁。ADHD根据《精神疾病诊断与统计手册》第四版（DSM-IV）标准，采用K-SADS-PL半结构化访谈进行诊断。据家长报告，对照组参与者无任何精神或发育障碍，且在ADHD评定量表-IV上的得分比年龄相适应的常模高出不到1.5个标准差。除中度或重度智力残疾外，未应用其他排除标准，以便该队列反映ADHD患者的典型横断面情况。
使用统计模式识别方法针对整个年龄范围和特定年龄范围开发了诊断分类器，并通过交叉验证以及应用于开发过程中未使用的单独一组记录进行了测试。年龄特异性分类方法比年龄非特异性版本更准确（独立测试队列中的准确率为76%；交叉验证准确率为81%）（分别为76%；73%）。发现实足年龄是一个重要的分类特征。
本文介绍的基于脑电图的分类方法的新应用，通过提高ADHD儿童和青少年的初始诊断准确性和持续监测水平，可为临床医生带来显著益处。年龄特异性分类器可在单个时间点获得最准确的诊断，但年龄非特异性分类器也很有用，因为它们能够对脑功能进行纵向监测。
