Clinical markers shaping the trajectory of bipolar disorder
[eng] INTRODUCTION: Bipolar disorder (BD) is a severe psychiatric disorder characterized by recurring mood episodes of depression or (hypo)mania with a prevalence in the general population of 2%. The clinical course and outcomes of BD are highly variable and heterogeneous. Indeed, the long- term tra...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad de Barcelona |
| Repositorio: | Dipòsit Digital de la UB |
| OAI Identifier: | oai:diposit.ub.edu:2445/214100 |
| Acceso en línea: | https://hdl.handle.net/2445/214100 http://hdl.handle.net/10803/691542 |
| Access Level: | acceso abierto |
| Palabra clave: | Trastorn bipolar Agressivitat Temperament Comorbiditat Manic-depressive illness Aggressiveness Comorbidity |
| Sumario: | [eng] INTRODUCTION: Bipolar disorder (BD) is a severe psychiatric disorder characterized by recurring mood episodes of depression or (hypo)mania with a prevalence in the general population of 2%. The clinical course and outcomes of BD are highly variable and heterogeneous. Indeed, the long- term trajectory of BD spans from lasting remission to recurrent severe mood symptoms, often leading to repeated hospitalizations and substantial healthcare costs. Given BD's inherent heterogeneity, the crucial question emerges of what is an individual's risk of enduring a severe course of illness. This thesis project is dedicated to exploring the role of predictive clinical markers in BD. We will scrutinize a range of clinical specifiers, including predominant polarity (PP), personality traits, duration of untreated illness (DUI), substance use, treatment response, and global factors influencing patterns of treatment prescription, aggressive behaviors, and functioning, to provide a comprehensive understanding of the course of BD. HYPOTHESES: The main hypotheses are that some clinical variables may be associated with poorer outcomes in BD and that clinical variables can be used to predict long-term outcomes in BD. More specifically we hypothesize that: 1) the presence of a PP in BD can serve as a valid course specifier that potentially enhances long-term management, whilst individuals with Undetermined PP (UPP) may represent a subgroup with a more severe course of the illness (study I); 2) affective temperaments, as enduring personality traits, may be associated with poorer outcomes in BD, possibly due to their link with aggressive behavior (study II); 3) A longer duration of untreated illness (DUI) is associated with a less favorable response to mood stabilizers, ultimately impacting overall global functioning in individuals with BD (study III); 4) patients with BD who frequently experience mixed episodes constitute a distinct sub- phenotype within the condition (study VI); 5) clinical variables can effectively predict sub- phenotypes of BD, specifically the presence of comorbidity with substance use disorder, using machine learning techniques (study IV); 6) clinical specifiers of BD may vary across different cohorts due to significant variability in global medical practice (study V). OBJECTIVES: The overarching goals of our research encompassed a comprehensive exploration of diverse aspects related to BD. Firstly, we aimed to delve into the socio-demographic, clinical, and treatment-related characteristics of individuals with Undetermined Predominant Polarity (UPP) and draw comparisons with those exhibiting Depressive Predominant Polarity (DPP) and Manic Predominant Polarity (MPP). Furthermore, we aimed to broaden the conceptualization of Predominant Polarity (PP) by incorporating mixed episodes, investigating whether patients with a specific PP were predisposed to experiencing mixed episodes. Moving beyond individual characteristics, our focus in another study was to identify and characterize intra-diagnostic subgroups among BD patients, with a specific emphasis on aggressive behavior. Within this context, we sought to evaluate the potential influence of affective temperament dimensions on the emergence and severity of aggressive behavior. Additionally, a distinct study delved into the intricate relationship between the duration of untreated illness (DUI), treatment response, and overall functioning in individuals diagnosed with BD. In an innovative approach, we endeavored to predict the presence of substance use disorders (SUD) within a substantial cohort of BD patients, leveraging the power of a machine learning algorithm fueled by various clinical variables. Lastly, we undertook a global examination of pharmacotherapeutic treatment patterns across diverse cohorts of well-characterized individuals with BD. This exploration sought to uncover disparities in prescription practices that could significantly impact the outcomes and trajectories of BD. |
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