Identification and initial validation of empirically derived bipolar symptom states from a large longitudinal dataset: an application of hidden Markov modeling to the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study.
Identification and initial validation of empirically derived bipolar symptom states from a large longitudinal dataset: an application of hidden Markov modeling to the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study.
复制标题
DOI：
10.1017/s0033291718002143
复制
发表时间：
2019-05
影响因子：
6.9
通讯作者：
DeSantis SM
中科院分区：
文献类型：
--
作者：
Prisciandaro JJ;Tolliver BK;DeSantis SM
虽然双相情感障碍（BD）从根本上说是一种周期性疾病，但自20世纪80年代出现以来，强调极性而非周期性的BD分裂模型一直主导着现代精神病诊断系统。然而，由于新出现的支持性数据，BD的概念化逐渐回归到研究界的纵向过程。纵向统计方法的进步有望进一步推动这一领域的发展。本研究采用隐马尔可夫模型从纵向数据（即，Young躁狂评定量表和Montgomery-Asberg抑郁评定量表在STEP-BD研究的5种情况下的反应），估计参与者随时间推移在这些状态之间转换的概率（n= 3，918），并评估临床变量（例如，快速循环，物质依赖）预测参与者的状态转换（n= 3，229）。分析确定了三种情绪状态（“情绪正常”，“抑郁”，“混合”）。相对于情绪正常和抑郁状态，混合状态不太常见，时间上更不稳定，并且与快速循环、物质使用和精神病唯一相关。在基线时被分配到混合状态的个体被诊断为BD-II（与BD-I相比）的可能性相对较小，更有可能出现混合或（低）躁狂发作，并且更频繁地报告经历易怒和情绪升高。本研究的结果代表了重要的一步，在定义和表征的纵向过程中，精神衍生的情绪状态，可用于形成的基础，客观的，经验的尝试，以确定有意义的亚型的情感疾病定义的临床过程。
Although Bipolar Disorder (BD) is a fundamentally cyclical illness, a divided model of BD that emphasizes polarity over cyclicity has dominated modern psychiatric diagnostic systems since their advent in the 1980s. However, there has been a gradual return to conceptualizations of BD which focus on longitudinal course in the research community due to emerging supportive data. Advances in longitudinal statistical methods promise to further progress the field. The present study employed hidden Markov modeling to uncover empirically-derived manic and depressive states from longitudinal data (i.e., Young Mania Rating Scale and Montgomery-Asberg Depression Rating Scale responses across 5 occasions from the STEP-BD study), estimate participants’ probabilities of transitioning between these states over time (n=3,918), and evaluate whether clinical variables (e.g., rapid cycling, substance dependence) predict participants’ state transitions (n=3,229). Analyses identified three empirically-derived mood states (“euthymic,” “depressed,” “mixed”). Relative to the euthymic and depressed states, the mixed state was less commonly experienced, more temporally unstable, and uniquely associated with rapid cycling, substance use, and psychosis. Individuals assigned to the mixed state at baseline were relatively less likely to be diagnosed with BD-II (vs. BD-I), more likely to present with a Mixed or (Hypo)Manic Episode, and reported experiencing irritable and elevated mood more frequently. The results from the present study represent an important step in defining, and characterizing the longitudinal course of, empirically-derived mood states that can be used to form the foundation of objective, empirical attempts to define meaningful subtypes of affective illness defined by clinical course.