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治疗抵抗性重性抑郁障碍和双相障碍患者对氯胺酮反应的预测因素。

Predictors of Response to Ketamine in Treatment Resistant Major Depressive Disorder and Bipolar Disorder.

机构信息

Mood Disorders Psychopharmacology Unit (MDPU), University Health Network, University of Toronto, Toronto, ON MT5 2S8, Canada.

Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada.

出版信息

Int J Environ Res Public Health. 2018 Apr 17;15(4):771. doi: 10.3390/ijerph15040771.

Abstract

OBJECTIVES

Extant evidence indicates that ketamine exerts rapid antidepressant effects in treatment-resistant depressive (TRD) symptoms as a part of major depressive disorder (MDD) and bipolar disorder (BD). The identification of depressed sub-populations that are more likely to benefit from ketamine treatment remains a priority. In keeping with this view, the present narrative review aims to identify the pretreatment predictors of response to ketamine in TRD as part of MDD and BD.

METHOD

Electronic search engines PubMed/MEDLINE, ClinicalTrials.gov, and Scopus were searched for relevant articles from inception to January 2018. The search term was cross-referenced with the terms , and and/or .

RESULTS

Multiple baseline pretreatment predictors of response were identified, including clinical (i.e., Body Mass Index (BMI), history of suicide, family history of alcohol use disorder), peripheral biochemistry (i.e., adiponectin levels, vitamin B12 levels), polysomnography (abnormalities in delta sleep ratio), neurochemistry (i.e., glutamine/glutamate ratio), neuroimaging (i.e., anterior cingulate cortex activity), genetic variation (i.e., Val66Met BDNF allele), and cognitive functioning (i.e., processing speed). High BMI and a positive family history of alcohol use disorder were the most replicated predictors.

CONCLUSIONS

A pheno-biotype of depression more, or less likely, to benefit with ketamine treatment is far from complete. Notwithstanding, metabolic-inflammatory alterations are emerging as possible pretreatment response predictors of depressive symptom improvement, most notably being cognitive impairment. Sophisticated data-driven computational methods that are iterative and agnostic are more likely to provide actionable baseline pretreatment predictive information.

摘要

目的

现有证据表明,氯胺酮作为重度抑郁症(MDD)和双相情感障碍(BD)的一部分,对治疗抵抗性抑郁(TRD)症状具有快速的抗抑郁作用。确定更有可能从氯胺酮治疗中获益的抑郁亚人群仍然是当务之急。鉴于此,本叙述性综述旨在确定 TRD 中氯胺酮治疗反应的预处理预测因子,作为 MDD 和 BD 的一部分。

方法

从开始到 2018 年 1 月,电子搜索引擎 PubMed/MEDLINE、ClinicalTrials.gov 和 Scopus 搜索了相关文章。搜索词与术语、和/或交叉参考。

结果

确定了多种基线预处理反应预测因子,包括临床(即体重指数(BMI)、自杀史、酒精使用障碍家族史)、外周生物化学(即脂联素水平、维生素 B12 水平)、多导睡眠图(δ睡眠比异常)、神经化学(即谷氨酰胺/谷氨酸比值)、神经影像学(即前扣带皮层活动)、遗传变异(即 Val66Met BDNF 等位基因)和认知功能(即处理速度)。高 BMI 和阳性酒精使用障碍家族史是最具重复性的预测因子。

结论

更有可能或不太可能从氯胺酮治疗中获益的抑郁表型远未完成。尽管如此,代谢-炎症改变正在成为抑郁症状改善的可能预处理反应预测因子,最显著的是认知障碍。迭代且不依赖于特定假设的复杂数据驱动计算方法更有可能提供可操作的基线预处理预测信息。

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