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      Clinical correlates of age at onset distribution in bipolar disorder: a comparison between diagnostic subgroups

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          Abstract

          Background

          Admixture analysis of age at onset (AAO) has helped delineating the clinical profile of early onset (EO) bipolar disorder (BD). However, there is scarce evidence comparing the distributional properties of AAO as well as the clinical features of EO BD type 1 (BD1) with EO BD type 2 (BD2). To this end, we studied 515 BD patients (224 BD1, 279 BD2, and 12 BD not otherwise specified [NOS]) diagnosed according to DSM-IV-TR criteria.

          Methods

          AAO was defined as the first reliably diagnosed hypo/manic or depressive episode according to diagnostic criteria. We used normal distribution mixture analysis to identify subgroups of patients according to AAO. Models were chosen according to the Schwarz’s Bayesian information criteria (BIC). Clinical correlates of EO were analysed using univariate tests and multivariate logistic regression models.

          Results

          A two normal components model best fitted the observed distribution of AAO in BD1 (BIC = −1599.3), BD2 (BIC = −2158.4), and in the whole sample (BIC = −3854.9). A higher number of EO BD2 patients had a depression-(hypo)mania-free interval (DMI) course, while a higher rate of (hypo)mania-depression-free interval (MDI) course was found in EO BD1. EO BD2 had also a higher rate of comorbidity with alcohol dependence compared to EO BD1. The latter finding was confirmed by multivariate logistic regression analysis.

          Conclusions

          In conclusion, both BD1 and BD2 had bimodal AAO distributions, but EO subgroups had a diagnostic-specific clinical delineation.

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          Most cited references32

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          Long-term implications of early onset in bipolar disorder: data from the first 1000 participants in the systematic treatment enhancement program for bipolar disorder (STEP-BD).

          Early onset of mood symptoms in bipolar disorder has been associated with poor outcome in many studies; however, the factors that might contribute to poor outcome have not been adequately investigated. The first consecutive 1000 adult bipolar patients enrolled in the National Institute of Mental Health's Systematic Treatment Enhancement Program for Bipolar Disorder were assessed at study entry to determine details of their age of onset of mood symptoms. Clinical course, comorbidity, and functional status and quality of life were compared for groups with very early (age 18 years) onset of mood symptoms. Of 983 subjects in whom age of onset could be determined, 272 (27.7%) experienced very early onset, and 370 (37.6%) experienced early onset. Earlier onset was associated with greater rates of comorbid anxiety disorders and substance abuse, more recurrences, shorter periods of euthymia, greater likelihood of suicide attempts and violence, and greater likelihood of being in a mood episode at study entry. Very early or early onset of bipolar disorder might herald a more severe disease course in terms of chronicity and comorbidity. Whether early intervention might modify this risk merits further investigation.
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            MCLUST: Software for Model-Based Cluster Analysis

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              Differences between bipolar I and bipolar II disorders in clinical features, comorbidity, and family history.

              The present study was designed to investigate whether bipolar II disorder (BP-II) has different characteristics from bipolar I disorder (BP-I), not only in manic severity but also in clinical features, prior course, comorbidity, and family history, sufficiently enough to provide its nosological separation from BP-I.
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                Author and article information

                Contributors
                +393404189755 , mirkomanchia@unica.it , Mirko.Manchia@dal.ca
                giuseppe.maina@unito.it
                bcarpini@iol.it
                fedepinna@inwind.it
                lucasteardo@gmail.com
                dambrosio.virginia@formamenti.it
                virginiosalvi@gmail.com
                malda@dal.ca
                alfonsotortorella@gmail.com
                umberto.albert@unito.it
                Journal
                Int J Bipolar Disord
                Int J Bipolar Disord
                International Journal of Bipolar Disorders
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                2194-7511
                21 August 2017
                21 August 2017
                2017
                : 5
                : 28
                Affiliations
                [1 ]ISNI 0000 0004 1755 3242, GRID grid.7763.5, Section of Psychiatry, Department of Medical Science and Public Health, , University of Cagliari, ; Via Liguria, 13, 09127 Cagliari, Italy
                [2 ]ISNI 0000 0004 1936 8200, GRID grid.55602.34, Department of Pharmacology, , Dalhousie University, ; Halifax, NS Canada
                [3 ]ISNI 0000 0001 2336 6580, GRID grid.7605.4, Department of Mental Health, “San Luigi-Gonzaga” Hospital, , University of Turin, ; Orbassano, Italy
                [4 ]ISNI 0000 0001 0790 385X, GRID grid.4691.a, Department of Psychiatry, , University of Naples SUN, ; Naples, Italy
                [5 ]ISNI 0000 0004 1936 8200, GRID grid.55602.34, Department of Psychiatry, , Dalhousie University, ; Halifax, NS Canada
                [6 ]ISNI 0000 0001 2336 6580, GRID grid.7605.4, Rita Levi Montalcini Department of Neuroscience, Anxiety and Mood Disorders Unit, , University of Turin, ; Turin, Italy
                Author information
                http://orcid.org/0000-0003-4175-6413
                Article
                97
                10.1186/s40345-017-0097-1
                5563503
                28480486
                96e7563a-57ca-4330-ba0e-3ec348d089e6
                © The Author(s) 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 6 January 2017
                : 26 April 2017
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                mood disorders,diagnostic subtypes,early onset,retrospective study,admixture analysis

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