2 results
Do antidepressants influence mood patterns? A naturalistic study in bipolar disorder
- M. Bauer, N. Rasgon, P. Grof, T. Glenn, M. Lapp, W. Marsh, R. Munoz, A. Suwalska, C. Baethge, T. Bschor, M. Alda, P.C. Whybrow
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- Journal:
- European Psychiatry / Volume 21 / Issue 4 / June 2006
- Published online by Cambridge University Press:
- 16 April 2020, pp. 262-269
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This prospective, longitudinal study compared the frequency and pattern of mood changes between outpatients receiving usual care for bipolar disorder who were either taking or not taking antidepressants. One hundred and eighty-two patients with bipolar disorder self-reported mood and psychiatric medications for 4 months using a computerized system (ChronoRecord) and returned 22,626 days of data. One hundred and four patients took antidepressants, 78 did not. Of the antidepressants taken, 95% were selective serotonin or norepinephrine reuptake inhibitors, or second-generation antidepressants. Of the patients taking an antidepressant, 91.3% were concurrently taking a mood stabilizer. The use of antidepressants did not influence the daily rate of switching from depression to mania or the rate of rapid cycling, independent of diagnosis of bipolar I or II. The primary difference in mood pattern was the time spent normal or depressed. Patients taking antidepressants frequently remained in a subsyndromal depression. In this naturalistic study using self-reported data, patients with bipolar disorder who were taking antidepressants—overwhelmingly not tricyclics and with a concurrent mood stabilizer—did not experience an increase in the rate of switches to mania or rapid cycling compared to those not taking antidepressants. Antidepressants had little impact on the mood patterns of bipolar patients taking mood stabilizers.
Influence of birth cohort on age of onset cluster analysis in bipolar I disorder
- M. Bauer, T. Glenn, M. Alda, O.A. Andreassen, E. Angelopoulos, R. Ardau, C. Baethge, R. Bauer, F. Bellivier, R.H. Belmaker, M. Berk, T.D. Bjella, L. Bossini, Y. Bersudsky, E.Y.W. Cheung, J. Conell, M. Del Zompo, S. Dodd, B. Etain, A. Fagiolini, M.A. Frye, K.N. Fountoulakis, J. Garneau-Fournier, A. Gonzalez-Pinto, H. Harima, S. Hassel, C. Henry, A. Iacovides, E.T. Isometsä, F. Kapczinski, S. Kliwicki, B. König, R. Krogh, M. Kunz, B. Lafer, E.R. Larsen, U. Lewitzka, C. Lopez-Jaramillo, G. MacQueen, M. Manchia, W. Marsh, M. Martinez-Cengotitabengoa, I. Melle, S. Monteith, G. Morken, R. Munoz, F.G. Nery, C. O’Donovan, Y. Osher, A. Pfennig, D. Quiroz, R. Ramesar, N. Rasgon, A. Reif, P. Ritter, J.K. Rybakowski, K. Sagduyu, A.M. Scippa, E. Severus, C. Simhandl, D.J. Stein, S. Strejilevich, A. Hatim Sulaiman, K. Suominen, H. Tagata, Y. Tatebayashi, C. Torrent, E. Vieta, B. Viswanath, M.J. Wanchoo, M. Zetin, P.C. Whybrow
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- Journal:
- European Psychiatry / Volume 30 / Issue 1 / January 2015
- Published online by Cambridge University Press:
- 15 April 2020, pp. 99-105
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Purpose:
Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.
Methods:The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.
Results:There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.
Conclusion:These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.