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Diagnosis and Management of Bipolar Disorder
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Diagnosis and Management of Bipolar Disorder

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Mental Health".

Deadline for manuscript submissions: closed (10 May 2024) | Viewed by 2546

Special Issue Editor

Dr. Giovanna Fico

E-Mail Website
Guest Editor
1. Bipolar and Depressive Disorders Unit, Hospìtal Clinic de Barcelona, c. Villarroel, 170, 08036 Barcelona, Spain
2. Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona (UB), c. Casanova, 143, 08036 Barcelona, Spain
Interests: bipolar disorder; mental illness; clinical psychiatry; psychopharmacology

Special Issue Information

Dear Colleagues,

Bipolar disorder is a severe psychiatric disorder characterized by recurring mood episodes of depression, alternating with episodes of euphoria (called manic/hypomanic episodes) with a prevalence in the general population of 2%. While we have made advancements in understanding the biological and environmental factors contributing to bipolar disorder, its diagnosis primarily relies on clinical assessment. Additionally, while there are established pharmacological treatment guidelines, many individuals, especially those with concurrent medical or psychiatric conditions, continue to experience frequent mood swings or persistent symptoms despite being on medication. A combined approach involving systematic clinical syndrome subtyping and the examination of multiple biomarkers, such as genetics and digital markers, could better define the unique characteristics of individuals with bipolar disorder and potentially predict the course of their illness.

In this Special Issue, we extend an invitation to researchers to submit their scientific and clinical contributions focusing on various aspects of bipolar disorder diagnosis and management. We welcome cutting-edge original research, comprehensive reviews, insightful case studies, and perspectives that explore genetic and digital phenotyping, as well as emerging pharmacological and non-pharmacological interventions for this condition. We also encourage submissions related to the integration of artificial intelligence in diagnostic algorithms and strategies for managing medical comorbidities or treatment-resistant bipolar depression. Our goal is to assemble a collection of impactful works that hold clinical significance in tailoring care for individuals with bipolar disorder throughout their lifespan.

Dr. Giovanna Fico
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • diagnostic challenges
  • biomarkers 
  • genetics 
  • digital phenotyping
  • substance abuse
  • medical comorbidities
  • personalization of care
  • treatment-resistant bipolar depression
  • artificial intelligence
  • precision medicine

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Published Papers (3 papers)

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Research

21 pages, 822 KiB  
Article
Automated Speech Analysis in Bipolar Disorder: The CALIBER Study Protocol and Preliminary Results
by Gerard Anmella, Michele De Prisco, Jeremiah B. Joyce, Claudia Valenzuela-Pascual, Ariadna Mas-Musons, Vincenzo Oliva, Giovanna Fico, George Chatzisofroniou, Sanjeev Mishra, Majd Al-Soleiti, Filippo Corponi, Anna Giménez-Palomo, Laura Montejo, Meritxell González-Campos, Dina Popovic, Isabella Pacchiarotti, Marc Valentí, Myriam Cavero, Lluc Colomer, Iria Grande, Antoni Benabarre, Cristian-Daniel Llach, Joaquim Raduà, Melvin McInnis, Diego Hidalgo-Mazzei, Mark A. Frye, Andrea Murru and Eduard Vietaadd Show full author list remove Hide full author list
J. Clin. Med. 2024, 13(17), 4997; https://doi.org/10.3390/jcm13174997 (registering DOI) - 23 Aug 2024
Abstract
Background: Bipolar disorder (BD) involves significant mood and energy shifts reflected in speech patterns. Detecting these patterns is crucial for diagnosis and monitoring, currently assessed subjectively. Advances in natural language processing offer opportunities to objectively analyze them. Aims: To (i) correlate [...] Read more.
Background: Bipolar disorder (BD) involves significant mood and energy shifts reflected in speech patterns. Detecting these patterns is crucial for diagnosis and monitoring, currently assessed subjectively. Advances in natural language processing offer opportunities to objectively analyze them. Aims: To (i) correlate speech features with manic-depressive symptom severity in BD, (ii) develop predictive models for diagnostic and treatment outcomes, and (iii) determine the most relevant speech features and tasks for these analyses. Methods: This naturalistic, observational study involved longitudinal audio recordings of BD patients at euthymia, during acute manic/depressive phases, and after-response. Patients participated in clinical evaluations, cognitive tasks, standard text readings, and storytelling. After automatic diarization and transcription, speech features, including acoustics, content, formal aspects, and emotionality, will be extracted. Statistical analyses will (i) correlate speech features with clinical scales, (ii) use lasso logistic regression to develop predictive models, and (iii) identify relevant speech features. Results: Audio recordings from 76 patients (24 manic, 21 depressed, 31 euthymic) were collected. The mean age was 46.0 ± 14.4 years, with 63.2% female. The mean YMRS score for manic patients was 22.9 ± 7.1, reducing to 5.3 ± 5.3 post-response. Depressed patients had a mean HDRS-17 score of 17.1 ± 4.4, decreasing to 3.3 ± 2.8 post-response. Euthymic patients had mean YMRS and HDRS-17 scores of 0.97 ± 1.4 and 3.9 ± 2.9, respectively. Following data pre-processing, including noise reduction and feature extraction, comprehensive statistical analyses will be conducted to explore correlations and develop predictive models. Conclusions: Automated speech analysis in BD could provide objective markers for psychopathological alterations, improving diagnosis, monitoring, and response prediction. This technology could identify subtle alterations, signaling early signs of relapse. Establishing standardized protocols is crucial for creating a global speech cohort, fostering collaboration, and advancing BD understanding. Full article
(This article belongs to the Special Issue Diagnosis and Management of Bipolar Disorder)
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12 pages, 249 KiB  
Article
Understanding Internalized Stigma’s Role in Sex-Specific Suicidal Ideation among Individuals with Bipolar Disorder
by Martina D’Angelo and Luca Steardo, Jr.
J. Clin. Med. 2024, 13(14), 4000; https://doi.org/10.3390/jcm13144000 - 9 Jul 2024
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Abstract
Background: The experience of stigma can exert a profound impact on the mental health and well-being of individuals with bipolar disorder (BD). Our study explores which factors of internalized stigma are associated with suicidal ideation and how they differ between the two [...] Read more.
Background: The experience of stigma can exert a profound impact on the mental health and well-being of individuals with bipolar disorder (BD). Our study explores which factors of internalized stigma are associated with suicidal ideation and how they differ between the two sexes in a clinical sample of BD patients. Methods: The study follows a cross-sectional study design, employing the Clinical Global Impression for Bipolar Patients (CGI-BP) to evaluate the overall severity of illness and the alteration in patients affected by bipolar disorder, the Internalized Stigma of Mental Illness (ISMI) assessing self-stigma among individuals experiencing mental disorders, and the Columbia Suicide Severity Rating Scale (C-SSRS) identifying and assessing individuals vulnerable to suicide. Descriptive analyses, analysis of variance (ANOVA), and logistic regression analysis were conducted, and 344 BD subjects were recruited. Results: Our ANOVA results revealed a significant association between sex and suicide across ISMI sub-items (p = 0.000). Logistic regression analysis comprised three phases: Discrimination was consistently significant across all phases (p < 0.001), while Alienation and Stereotype emerged as additional predictors of suicide in later phases of the analysis (p < 0.001). Conclusions: Our study contributes to the growing body of literature on internalized stigma, sex, and suicidality among individuals with bipolar disorder. Early intervention programs and prevention strategies are needed. Full article
(This article belongs to the Special Issue Diagnosis and Management of Bipolar Disorder)
11 pages, 2175 KiB  
Article
The Mixed Tendency in Bipolar Disorder: An Operational Proposal for the Integration of Mixed Episodes in Predominant Polarity
by Giovanna Fico, Gerard Anmella, Michele De Prisco, Vincenzo Oliva, Chiara Possidente, Lorenzo Bracco, Marta Bort, Tabatha Fernandez-Plaza, Anna Giménez-Palomo, Eduard Vieta and Andrea Murru
J. Clin. Med. 2023, 12(23), 7398; https://doi.org/10.3390/jcm12237398 - 29 Nov 2023
Cited by 1 | Viewed by 1106
Abstract
Predominant Polarity (PP) is an established specifier of Bipolar Disorder (BD), holding significant clinical implications. Nevertheless, there exists no consensus on how to incorporate mixed states into PP, leaving patients prone to mixed recurrences that are unclassified. In a comprehensive study involving 701 [...] Read more.
Predominant Polarity (PP) is an established specifier of Bipolar Disorder (BD), holding significant clinical implications. Nevertheless, there exists no consensus on how to incorporate mixed states into PP, leaving patients prone to mixed recurrences that are unclassified. In a comprehensive study involving 701 euthymic BD patients, we sought to redefine PP by introducing a novel metric, the “mixed tendency”, and establish a practical threshold to identify patients with a “mixed phenotype”. Furthermore, we investigated potential associations between the mixed phenotype and specific PP categories. Our findings revealed that the mixed tendency correlated significantly with early BD type I, lifetime suicide attempts, self-aggressive behaviour, and lifetime number of affective episodes (>5). Using a ROC curve analysis, we determined an optimal cut-off point for the mixed tendency at 0.228, suggesting that patients with ~25% of lifetime mixed episodes relative to total affective episodes should be identified as having a mixed phenotype. Notably, the mixed phenotype was positively associated with undetermined PP and negatively with manic and depressive PP. This study introduces a promising approach to incorporating mixed episodes into the PP definition, potentially enabling tailored interventions for patients with a substantial history of mixed episodes. However, further research in large, longitudinal cohorts is essential to validate these findings. Full article
(This article belongs to the Special Issue Diagnosis and Management of Bipolar Disorder)
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