Classification of adolescent psychotic disorders using linear discriminant analysis

被引:37
作者
Pardo, Patricia J.
Georgopoulos, Apostolos P.
Kenny, John T.
Stuve, Traci A.
Findling, Robert L.
Schulz, S. Charles
机构
[1] Domenici Res Ctr Mental Illness, Brain Sci Ctr, Minneapolis Vet Affairs Med Ctr, Minneapolis, MN 55417 USA
[2] Univ Minnesota, Sch Med, Dept Psychiat, Minneapolis, MN 55454 USA
[3] Univ Minnesota, Dept Psychol, Minneapolis, MN 55455 USA
[4] Univ Minnesota, Sch Med, Dept Neurosci, Minneapolis, MN 55455 USA
[5] Univ Minnesota, Sch Med, Dept Neurol, Minneapolis, MN 55455 USA
[6] Univ Minnesota, Ctr Cognit Sci, Minneapolis, MN 55455 USA
[7] Louis Stokes Vet Affairs Med Ctr, Cleveland, OH 44106 USA
[8] Case Western Reserve Univ, Dept Psychol, Cleveland, OH 44106 USA
[9] Case Western Reserve Univ, Dept Psychiat, Cleveland, OH 44106 USA
关键词
schizophrenia; bipolar disorder; LDA; neuropsychological; MRI; diagnosis;
D O I
10.1016/j.schres.2006.05.007
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
Background: The differential diagnosis between schizophrenia and bipolar disorder during adolescence presents a major clinical problem. Can these two diagnoses be differentiated objectively early in the courses of illness? Methods: We used linear discrimination analysis (LDA) to classify 28 adolescent subjects into one of three diagnostic categories (healthy, N=8; schizophrenia, N=10; bipolar, N=10) using subsets from a pool of 45 variables as potential predictors (22 neuropsychological test scores and 23 quantitative structural brain measurements). The predictor variables were adjusted for age, gender, race, and psychotropic medication. All possible subsets composed of k=2-12 variables, from the set of 45 variables available, were evaluated using the robust leaving-one-subject-out method. Results: The highest correct classification (96%) of the 3 diagnostic categories was yielded by 9 sets of k=12 predictors, comprising both neuropsychological and brain structural measures. Although each one of these sets misclassified one case, each set correctly classified (100%) at least one group, such that a fully correct diagnosis could be reached by a tree-type decision procedure. Conclusions: We conclude that LDA with 12 predictor variables can provide correct and robust classification of subjects into the three diagnostic categories above. This robust classification relies upon both neuropsychological and brain structural information. Our results demonstrate that, despite overlapping clinical symptoms, schizophrenia and bipolar disorder can be differentiated early in the course of disease. This finding has two important implications. Firstly, schizophrenia and bipolar disorder are different illnesses. If schizophrenia and bipolar are dissimilar clinical manifestations of the same disease, we would not be able to use non-clinical information to classify ('diagnose') schizophrenia and bipolar disorder. Secondly, if this study's findings are replicated, brain structure (MRI) and brain function (neuropsychological) used together may be useful in the diagnosis of new patients. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:297 / 306
页数:10
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