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帕金森患者抑郁及认知功能障碍的临床特点及影响因素分析 被引量:3

Clinical characteristics of depression and cognitive dysfunction in patients with Parkinson′s disease and analysis of related factors
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摘要 目的探讨帕金森患者抑郁及认知功能障碍(CI)的临床特征并分析伴抑郁或CI的影响因素。方法127例帕金森患者,抑郁评估采用老年抑郁自评量表(GDS),调查患者抑郁临床特征并分析影响因素;认知功能评估采用蒙特利尔认知评估量表(MOCA),调查患者CI临床特征并分析影响因素。结果127例帕金森患者GDS评分为(15.38±4.27)分,抑郁发生率为59.06%,病程、CI、Hoehn-Yahr分期是患者抑郁的影响因素(P<0.05);MoCA评分为(25.93±4.27),CI发生率为52.76%,CI的影响因素包括文化程度、Hoehn-Yahr分期、抑郁(P<0.05)。结论帕金森患者抑郁及CI发生率相对较高,不仅受到Hoehn-Yahr分期等因素影响,两者也会互相影响。 Objective To investigate the clinical characteristics of depression and cognitive impairment(CI)in patients with Parkinson′s disease and analyze their influencing factors.Methods One hundred and twenty-seven patients with Parkinson′s disease were selected as research subjects.Geriatric Depression Scale(GDS)and Montreal Cognitive Assessment(MOCA)scale were used to evaluate depression and cognitive function,respectively.The clinical characteristics of depression and CI were investigated and influencing factors were analyzed.Results The average GDS score was(15.38±4.27),and the incidence of depression was 59.06%.Course of disease,CI and Hoehn-Yahr staging were influencing factors of depression(P<0.05).The average MoCA score was(25.93±4.27),and the incidence of CI was 52.76%.Educational level,Hoehn-Yahr staging and depression were influencing factors of CI(P<0.05).Conclusions The incidence rates of depression and CI are higher in patients with Parkinson′s disease.Depression and CI are not only susceptible to many factors like Hoehn-Yahr staging,but the two will also affect each other.It needs to be paid attention.
作者 蔡竹清 唐春梅 曾敏 CAI Zhu-qing;TANG Chun-mei;ZENG Min(General Medicine Department,Suining Central Hospital,Suining 629000,China;Department of Neurology,West China Hospital,Sichuan University,Chengdu 610041,China)
出处 《实用医院临床杂志》 2023年第3期125-129,共5页 Practical Journal of Clinical Medicine
基金 四川省基层卫生事业发展研究中心项目(编号:SWFZ20-Q-058)。
关键词 帕金森 抑郁 认知功能障碍 临床特点 因素分析 Parkinson′s disease Depression Cognitive impairment Clinical characteristic Factor analysis
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