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临床特征对酒精依赖复发的影响:前瞻性队列研究

  • 朱冉 ,
  • 倪照军 ,
  • 张顺 ,
  • 庞良俊 ,
  • 王传升 ,
  • 鲍彦平 ,
  • 孙洪强
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孙洪强,教授,主任医师,博士生导师,北京大学第六医院副院长,北京大学精神卫生研究所副所长。
从事精神疾病的临床和基础研究工作20余年,主要研究领域为睡眠障碍治疗、睡眠与奖赏记忆、成瘾心理渴求的神经机制和干预。近几年在Addiction biology,Sleep Psychoneuroendo-crinology等期刊发表论文60余篇,其中多篇被Biology Psychiatry、Journal of Neuroscience等权威杂志引用。参编参译《沈渔邨精神病学》《酒精使用相关障碍临床诊疗指南》《睡眠与睡眠障碍相关量表》等18部著作。主持和参与多项国家自然科学基金、973计划、国家科技支撑计划等项目。
现任中国医师协会精神科医师分会精准医疗专委会和睡眠医学专委会副主委,中国毒理学会药物依赖性毒理学专业委员会副主委,中国老年学和老年医学学会睡眠科学分会副主任委员,北京医学伦理学会副理事长,中国医师协会精神科医师分会委员,中国毒品滥用防治专家委员会委员等。

收稿日期: 2019-03-19

  网络出版日期: 2019-06-26

基金资助

国家自然科学基金(81571297)

Effect of clinical characteristics on relapse of alcohol dependence: a prospective cohort study

  • Ran ZHU ,
  • Zhao-jun NI ,
  • Shun ZHANG ,
  • Liang-jun PANG ,
  • Chuan-sheng WANG ,
  • Yan-ping BAO ,
  • Hong-qiang SUN
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Received date: 2019-03-19

  Online published: 2019-06-26

Supported by

Supported by the National Natural Science Foundation of China(81571297)

摘要

目的 探讨人口学因素和心理渴求对酒精依赖患者复发的影响。方法 采用前瞻性研究方法,选择2017年8月至2018年8月在3家精神专科医院招募符合《美国精神疾病诊断与统计手册》第4版(Diagnositic and Statistical Manual Disorder-Fourth Version, DSM-Ⅳ)酒精依赖诊断标准的住院治疗的男性患者158例,进行基线测查,并在基线后3个月进行随访,调查复饮情况。基线测查包括人口学资料、饮酒特征、临床机构酒精依赖戒断评估表(clinical institute withdrawal assessment-advanced revised, CIWA-Ar)、环境线索诱导及戒断期心理渴求视觉模拟标尺评分(visual analog scale,VAS)、密歇根酒精依赖筛查量表(Michigan alcoholism screening test, MAST)、焦虑自评量表(self-rating anxiety scale, SAS)、抑郁自评量表(self-rating depression scale, SDS)及饮酒促迫性量表(alcohol urge questionnaire, AUQ)。根据随访结果,将“复发”定义为在基线和随访之间任何时刻饮用含有乙醇的饮料,“复发时间”定义为首次饮酒距离基线的天数。是否复发和复发时间是主要结局指标,采用Cox比例风险回归模型分析影响酒精依赖复发的因素。结果酒精依赖患者3个月复发率为63.7%, 多因素Cox比例风险回归模型分析发现年龄(OR=0.975,P=0.030)及CIWA-Ar评分(OR=1.126,P=0.010)是影响酒精依赖复发的因素,两种环境下心理渴求与复饮差异无统计学意义(P > 0.05)。结论 年龄与住院期间酒精依赖戒断症状严重程度是酒精依赖复发的影响因素,其中年龄大是保护因素,戒断症状的严重程度重是危险因素,而线索诱导及戒断期心理渴求对酒精依赖患者复发的影响作用较小。

本文引用格式

朱冉 , 倪照军 , 张顺 , 庞良俊 , 王传升 , 鲍彦平 , 孙洪强 . 临床特征对酒精依赖复发的影响:前瞻性队列研究[J]. 北京大学学报(医学版), 2019 , 51(3) : 519 -524 . DOI: 10.19723/j.issn.1671-167X.2019.03.021

Abstract

Objective: To investigate whether craving and demographic factors to predict relapse in alcohol dependence.Methods: This study was a prospective cohort study. From August 2017 to August 2018, 158 Han male inpatients who met the diagnositic and statistical manual disorders-fourth version(DSM-Ⅳ) alcohol dependence diagnostic criteria were recruited from three mental hospitals in China. The participants were interviewed at baseline and followed up by telephone after 3 months for assessment. The baseline assessment after the acute withdrawal period included demographic data and alcohol-related data, clinical institute withdrawal assessment-advanced revised (CIWA-Ar), withdrawal and cue-induced craving on visual analog scale (VAS), Michigan alcoholism screening test (MAST), self-rating anxiety scale (SAS), self-rating depression scale (SDS) and alcohol urge questionnaire (AUQ). According to the follow-up results, “relapse” was defined as the consumption of beverages containing ethanol at any time during the follow-up study, and “time to relapse” was defined as the number of days from the first drinking to the baseline. Whether relapse occurred and the time to relapse were the primary endpoints. Cox proportional hazard regression model was used to analyze the factors affecting the relapse of alcohol dependence. Results: In the study, 158 alcohol dependence patients were finally included, age from 21 to 60 years, with the mean age of (40.31±9.14) years. The relapse rate was 63.7% three months after baseline assessment. According to Cox univariate analysis and multivariate analysis, the age (OR=0.975, P=0.030) and CIWA-Ar scores (OR=1.126, P=0.010) significantly predicted relapse. And there was no significant difference in education level, marital status, withdrawal and cue-induced craving on VAS, SAS and SDS between the relapse group and the non-relapse group (P>0.05).Conclusion: Age and severity of alcohol-dependent withdrawal symptoms during hospitalization are significantly related to relapse for alcohol in alcohol-dependent patients. To be exact, the older age is a protective factor, that is to say, the younger patients are prone to relapse, while the risk of relapse is raised by the higher se-verity of withdrawal symptoms. However, neither cue-induced nor withdrawal craving can predict relapse of alcohol-dependent patients.

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