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首发双相情感障碍起病年龄的混合分析

Admixture analysis of age at onset in first episode bipolar disorder.

作者信息

Nowrouzi Behdin, McIntyre Roger S, MacQueen Glenda, Kennedy Sidney H, Kennedy James L, Ravindran Arun, Yatham Lakshmi, De Luca Vincenzo

机构信息

Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Centre for Research in Occupational Safety and Health, Laurentian University, Sudbury, Ontario, Canada.

Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; University Health Network in Toronto, Ontario, Canada.

出版信息

J Affect Disord. 2016 Sep 1;201:88-94. doi: 10.1016/j.jad.2016.04.006. Epub 2016 Apr 27.

Abstract

BACKGROUND

Many studies have used the admixture analysis to separate age-at-onset (AAO) subgroups in bipolar disorder, but none of them examined first episode patients.

OBJECTIVE

The purpose of this study was to investigate the influence of clinical variables on AAO in first episode bipolar patients.

METHODS

The admixture analysis was applied to identify the model best fitting the observed AAO distribution of a sample of 194 patients with DSM-IV diagnosis of bipolar disorder and the finite mixture model was applied to assess the effect of clinical covariates on AAO.

RESULTS

Using the BIC method, the model that was best fitting the observed distribution of AAO was a mixture of three normal distributions. We identified three AAO groups: early age-at-onset (EAO) (µ=18.0, σ=2.88), intermediate-age-at-onset (IAO) (µ=28.7, σ=3.5), and late-age-at-onset (LAO) (µ=47.3, σ=7.8), comprising 69%, 22%, and 9% of the sample respectively. Our first episode sample distribution model was significantly different from most of the other studies that applied the mixture analysis.

LIMITATIONS

The main limitation is that our sample may have inadequate statistical power to detect the clinical associations with the AAO subgroups.

CONCLUSIONS

This study confirms that bipolar disorder can be classified into three groups based on AAO distribution. The data reported in our paper provide more insight into the diagnostic heterogeneity of bipolar disorder across the three AAO subgroups.

摘要

背景

许多研究已使用混合分析来区分双相情感障碍的发病年龄(AAO)亚组,但均未对首发患者进行研究。

目的

本研究旨在探讨临床变量对首发双相情感障碍患者AAO的影响。

方法

应用混合分析来确定最适合194例符合DSM-IV双相情感障碍诊断的患者样本中观察到的AAO分布的模型,并应用有限混合模型来评估临床协变量对AAO的影响。

结果

使用贝叶斯信息准则(BIC)方法,最适合观察到的AAO分布的模型是三个正态分布的混合。我们确定了三个AAO组:早发型(EAO)(μ = 18.0,σ = 2.88)、中发型(IAO)(μ = 28.7,σ = 3.5)和晚发型(LAO)(μ = 47.3,σ = 7.8),分别占样本的69%、22%和9%。我们的首发样本分布模型与大多数其他应用混合分析的研究显著不同。

局限性

主要局限性在于我们的样本可能缺乏足够的统计效力来检测与AAO亚组的临床关联。

结论

本研究证实双相情感障碍可根据AAO分布分为三组。我们论文中报告的数据为双相情感障碍在三个AAO亚组中的诊断异质性提供了更多见解。

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