title: A predictive model for diagnosing bipolar disorder based on the clinical characteristics of major depressive episodes in Chinese population.
abstract: BACKGROUND
  A correct timely diagnosis of bipolar depression remains a big challenge for clinicians. This study aimed to develop a clinical characteristic based model to predict the diagnosis of bipolar disorder among patients with current major depressive episodes.
  
  
  METHODS
  A prospective study was carried out on 344 patients with current major depressive episodes, with 268 completing 1-year follow-up. Data were collected through structured interviews. Univariate binary logistic regression was conducted to select potential predictive variables among 19 initial variables, and then multivariate binary logistic regression was performed to analyze the combination of risk factors and build a predictive model. Receiver operating characteristic (ROC) curve was plotted.
  
  
  RESULTS
  Of 19 initial variables, 13 variables were preliminarily selected, and then forward stepwise exercise produced a final model consisting of 6 variables: age at first onset, maximum duration of depressive episodes, somatalgia, hypersomnia, diurnal variation of mood, irritability. The correct prediction rate of this model was 78% (95%CI: 75%-86%) and the area under the ROC curve was 0.85 (95%CI: 0.80-0.90). The cut-off point for age at first onset was 28.5 years old, while the cut-off point for maximum duration of depressive episode was 7.5 months.
  
  
  CONCLUSIONS
  The limitations of this study include small sample size, relatively short follow-up period and lack of treatment information.
  
  
  CONCLUSIONS
  Our predictive models based on six clinical characteristics of major depressive episodes prove to be robust and can help differentiate bipolar depression from unipolar depression.
authors.affiliation: Department of Psychiatry, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China.
authors.forename: Zhaoyu
authors.initials: Z
authors.lastname: Gan
authors.forename: Feici
authors.initials: F
authors.lastname: Diao
authors.forename: Qinling
authors.initials: Q
authors.lastname: Wei
authors.forename: Xiaoli
authors.initials: X
authors.lastname: Wu
authors.forename: Minfeng
authors.initials: M
authors.lastname: Cheng
authors.forename: Nianhong
authors.initials: N
authors.lastname: Guan
authors.forename: Ming
authors.initials: M
authors.lastname: Zhang
authors.forename: Jinbei
authors.initials: J
authors.lastname: Zhang
mesh_terms: D000328:Adult; D001714:Bipolar Disorder / Q000175:diagnosis* / Q000523:psychology*; D002681:China; D003866:Depressive Disorder / Q000175:diagnosis; D003865:Major Depressive Disorder / Q000175:diagnosis* / Q000523:psychology; D003937:Diagnosis, Differential; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007508:Irritable Mood; D008297:Male; D008960:Models, Psychological; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012016:Reference Values; D012307:Risk Factors