Detection Study of Bipolar Depression Through the Application of a Model-Based Algorithm in Terms of Clinical Feature and Peripheral Biomarkers

Conclusion: It seems to be feasible to combine different types of clinical characteristics with biomarkers in order to detect bipolarity of all depressive episodes. Neurotrophic factors of our interest presented its stable discriminant potentiality in unipolar and bipolar depression, deserving validation analysis in larger samples.IntroductionThe Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) separates the mood disorders into two sections: depressive and related disorders, and bipolar and related disorders. The new version of the diagnostic manual of bipolar disorders emphasizes more specific manifestations related to hypomanic and mixed manic states, which are considered to be a separate class of mood disorder “in terms of symptomatology, family history and genetics” (1–3). From a statistical point of view, the nature of the diagnostic classification of depressive disorder can be clearly taken as a typical dichotomous problem with only two possible outcomes: one is bipolar depressive disorder (BPD) and the other is major depressive disorder (MDD).In spite of its clear-cut division in diagnostic manual, a definite diagnosis for bipolar disorder remains an elusive goal. In a 10-year follow-up study of 290 unipolar depressed patients, Holmskov et al. have reported that the overall risk of conversion from initial diagnosis of unipolar depression to later bipolar disorder reaches up to 20.7% (4). The major challenge for clinical dec...
Source: Frontiers in Psychiatry - Category: Psychiatry Source Type: research

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