Background: Many people with bipolar disorder (BD) in the community are misdiagnosed with major depressive disorder (MDD). A probabilistic model has been proposed to assist in the identification of BD among patients with depressive symptoms, however there are limited population-based data on the key potential distinguishers of BD from MDD. The objective of this study was to identify distinguishers of BD from MDD in a population-based sample.
Methods: Population-based data were extracted from the Canadian Community Health Survey: Mental Health and Well-Being. Sociodemographic variables, clinical variables, and depressive symptomatology were compared between subjects with BD (N = 467) and MDD (N = 4145). Logistic regression analysis was used to identify significant correlates of BD, and areas under the receiver operating characteristic curves (AUCs) were determined for each model.
Results: BD and MDD subjects differed across a number of characteristics. Clinical variables significantly associated with BD included greater number of lifetime depressive episodes, earlier age of first depressive episode, lifetime anxiety disorder, problematic substance use, and lifetime suicide attempt. Depressive symptoms significantly more common in BD included agitation, suicidal ideation, anxious symptoms, and irritability. AUCs for these models ranged from 0.72 to 0.81.
Conclusions: These population-based results support the effort to establish a probabilistic model to assist in diagnosing BD that incorporates a number of clinical variables and depressive symptoms. Future studies are needed to prospectively determine the diagnostic accuracy of these distinguishers in generalizable samples, and to determine their potential benefit in decreasing rates of misdiagnosis of BD.