Dissimilar morbidity following initial mania versus mixed-states in type-I bipolar disorder

J Affect Disord. 2010 Oct;126(1-2):299-302. doi: 10.1016/j.jad.2010.03.014. Epub 2010 Apr 27.

Abstract

Background: Mixed-states of bipolar disorders (BPD) may predict worse future illness and more depressive than manic morbidity, challenging a tendency to conflate mixed-states and mania.

Methods: Patients (N=247) were followed-up systematically for 24 months following hospitalization for initial major episodes of DSM-IV type-I BPD and scored for weekly interval morbidity-types.

Results: Overall morbidity during follow-up was 1.6-times greater following mixed (n=97) versus manic (n=150) first-episodes of BPD (60.0 vs. 37.8%-of-weeks; p<0.0001). Patients with initial mixed-states had a nearly 12-fold later excess of mixed-states, 6.5-times more major depression, and 69% more dysthymia during follow-up than those presenting in mania. In contrast, manic first-episodes were followed by over 10-times more mania, 6-times more hypomania, and 35% more psychotic illness.

Limitations: Estimates of longitudinal morbidity may be inaccurate, and ongoing treatment may distort them.

Conclusions: Based on detailed, prospective assessments among first-episode BPD patients, those presenting in mixed-states were more ill, and much more likely to experience mixed, depressive and dysthymic morbidity during follow-up, versus much more mania, hypomania, and perhaps more psychosis following mania. The findings support two markedly dissimilar subtypes of BPD, and call for more explicit therapeutic studies of mixed-states.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Analysis of Variance
  • Bipolar Disorder / psychology*
  • Chi-Square Distribution
  • Depressive Disorder, Major / psychology
  • Disease Progression
  • Dysthymic Disorder / psychology
  • Female
  • Hospitalization / statistics & numerical data
  • Humans
  • Male
  • Psychiatric Status Rating Scales
  • Time Factors