Literature DB >> 36073706

The clinical characterization of the adult patient with bipolar disorder aimed at personalization of management.

Roger S McIntyre1,2,3, Martin Alda4,5, Ross J Baldessarini6,7,8, Michael Bauer9, Michael Berk10,11, Christoph U Correll12,13,14, Andrea Fagiolini15, Kostas Fountoulakis16, Mark A Frye17, Heinz Grunze18,19, Lars V Kessing20,21, David J Miklowitz22, Gordon Parker23, Robert M Post24,25, Alan C Swann26, Trisha Suppes27, Eduard Vieta28, Allan Young29,30, Mario Maj31.   

Abstract

Bipolar disorder is heterogeneous in phenomenology, illness trajectory, and response to treatment. Despite evidence for the efficacy of multimodal-ity interventions, the majority of persons affected by this disorder do not achieve and sustain full syndromal recovery. It is eagerly anticipated that combining datasets across various information sources (e.g., hierarchical "multi-omic" measures, electronic health records), analyzed using advanced computational methods (e.g., machine learning), will inform future diagnosis and treatment selection. In the interim, identifying clinically meaningful subgroups of persons with the disorder having differential response to specific treatments at point-of-care is an empirical priority. This paper endeavours to synthesize salient domains in the clinical characterization of the adult patient with bipolar disorder, with the overarching aim to improve health outcomes by informing patient management and treatment considerations. Extant data indicate that characterizing select domains in bipolar disorder provides actionable information and guides shared decision making. For example, it is robustly established that the presence of mixed features - especially during depressive episodes - and of physical and psychiatric comorbidities informs illness trajectory, response to treatment, and suicide risk. In addition, early environmental exposures (e.g., sexual and physical abuse, emotional neglect) are highly associated with more complicated illness presentations, inviting the need for developmentally-oriented and integrated treatment approaches. There have been significant advances in validating subtypes of bipolar disorder (e.g., bipolar I vs. II disorder), particularly in regard to pharmacological interventions. As with other severe mental disorders, social functioning, interpersonal/family relationships and internalized stigma are domains highly relevant to relapse risk, health outcomes, and quality of life. The elevated standardized mortality ratio for completed suicide and suicidal behaviour in bipolar disorder invites the need for characterization of this domain in all patients. The framework of this paper is to describe all the above salient domains, providing a synthesis of extant literature and recommendations for decision support tools and clinical metrics that can be implemented at point-of-care.
© 2022 World Psychiatric Association.

Entities:  

Keywords:  Bipolar disorder; bipolar I disorder; bipolar II disorder; clinical characterization; cognition; comorbidity; depression; mania; mixed features; personalization; phenotyping; rapid cycling; resilience; social determinants; stigma; stressors; subtypes; trauma

Year:  2022        PMID: 36073706      PMCID: PMC9453915          DOI: 10.1002/wps.20997

Source DB:  PubMed          Journal:  World Psychiatry        ISSN: 1723-8617            Impact factor:   79.683


  357 in total

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5.  Differentiation in the preonset phases of schizophrenia and mood disorders: evidence in support of a bipolar mania prodrome.

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Review 6.  The International Society for Bipolar Disorders (ISBD) Task Force report on the nomenclature of course and outcome in bipolar disorders.

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Journal:  Psychiatry Res       Date:  1986-05       Impact factor: 3.222

8.  Pediatric bipolar disorder: phenomenology and course of illness.

Authors:  Gianni L Faedda; Ross J Baldessarini; Ira P Glovinsky; Nancy B Austin
Journal:  Bipolar Disord       Date:  2004-08       Impact factor: 6.744

9.  The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality.

Authors:  John Torous; Sandra Bucci; Imogen H Bell; Lars V Kessing; Maria Faurholt-Jepsen; Pauline Whelan; Andre F Carvalho; Matcheri Keshavan; Jake Linardon; Joseph Firth
Journal:  World Psychiatry       Date:  2021-10       Impact factor: 49.548

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