PDF(Pubmed)
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.
摘要：
双相情感障碍在现象学上是异质的，疾病轨迹,以及对治疗的反应。尽管有证据表明多模式干预措施的有效性，受这种疾病影响的大多数人无法实现并维持完全的综合康复。人们热切期待将各种信息源的数据集(例如，分层“多元”措施，电子健康记录)，使用先进的计算方法进行分析(例如，机器学习)，将为未来的诊断和治疗选择提供信息。在此期间，在临床上确定对特定治疗有不同反应的疾病患者的有临床意义的亚组是经验上的优先事项。本文致力于合成成年双相情感障碍患者临床特征的显着域，其总体目标是通过告知患者管理和治疗注意事项来改善健康结果。现有数据表明，在双相情感障碍中表征选择领域可提供可操作的信息并指导共享决策。例如,这是强有力的确定，混合特征的存在-特别是在抑郁发作期间-以及身体和精神合并症告知疾病轨迹，对治疗的反应，和自杀风险。此外,早期环境暴露(例如，性虐待和身体虐待,情感忽视)与更复杂的疾病表现高度相关，邀请需要以发展为导向和综合的治疗方法。在验证双相情感障碍的亚型方面取得了重大进展(例如，I型双极与II无序)，特别是在药物干预方面。和其他严重的精神障碍一样，社会功能,人际关系/家庭关系和内化的污名化是与复发风险高度相关的领域，健康结果，和生活质量。双相情感障碍中完全自杀和自杀行为的标准化死亡率升高，需要在所有患者中对该领域进行表征。本文的框架是描述上述所有突出的领域，提供现有文献和建议的综合决策支持工具和临床指标，可以在护理点实施。
