【摘要】 目的:双相障碍与单相抑郁是两种不同的疾病,具有不同的发病机制,临床治疗方法也不相同,临床上早期区分却存在很大难度。本文探讨Fisher判别分析(FDA)方法在双相障碍早期识别中的应用,以达到早期区分单相抑郁和双相障碍的目的。方法:样本数据分为两组,包括复发抑郁组144例及双相障碍组107例;通过对两组间的一般人口学资料及临床特征进行统计学分析,筛选出具有显著差别的9个变量作为Fisher判别分析的观测变量;随机抽取部分案例作为训练样本,其它作为测试样本,针对训练样本,建立Fisher线性判别函数模型,并采用回代估计法计算误判率;将所建立的FDA模型用于测试样本的预测。结果:两组在年龄、性别、文化程度、家庭情况等一般人口学资料方面无显著性差异,而在HAMD、HAMA、YMRS、MDQ、HCL等9个变量间存在显著性差异。将此9个变量作为观测变量,建立最终的Fisher判别函数模型,此模型对于训练样本的预测正确率为81.6%,对于测试样本的预测正确率为74.2%。结论:Fisher判别函数模型检验结果与实际情况吻合良好,能够用于双相障碍的早期识别中。更多还原

【Abstract】 Objective It is generally accepted that bipolar disorder and unipolar depression are two different diseases for they have different pathogenesis and clinical treatment. There is a big difficulty in early identification between bipolar disorder and unipolar depression. This paper is to discuss the application of Fishier discriminant analysis(FDA) method in early recognition of bipolar disorder, in order to achieve the purpose of distinguishing between unipolar depression and bipolar disorder at the early stage. Methods 251 cases were selected in this study, including 144 cases with recurrent depression and 107 cases with bipolar disorder. General demographic dada and clinical features were statistically analyzed between the two groups. 9 variables with significant differences were screened as the observation variables of the Fisher discriminant analysis. Part of the sample were randomly selected as the training sample, the other as the test sample. Fisher linear discriminant function model was established according to the training sample, and the back substitution estimation method was used for calculating the misjudgment rate. The established FDA model can be further used for prediction of the test sample. Results The difference of age, gender, educational level and family status between the two groups had no statistical significance. While the difference of HAMD, HAMA, YMRS, MDQ and HCL was statistically significant. The Fisher linear discriminant function model was established based on 9 observation variables, the misjudgment rate of this model for the training sample was 18.4%, the forecast accuracy for the test sample was 74.2%. Conclusion The test results of Fisher discriminant function model are in good agreement with those obtained from the actual situation, and the Fisher discriminant function can be used for early recognition of bipolar disorder.更多还原