茶多酚对帕金森病猴多巴胺能神经元保护作用的研究

目的 探索茶多酚对1-甲基-4-苯基-1,2,3,6-四氢吡啶(1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, MPTP)诱导的帕金森病猴神经元的保护作用及机制。方法 健康雌性食蟹猴年龄10~12岁,采用数字表法随机分为4组:正常对照组、茶多酚对照组(TP组)、帕金森病模型组(MPTP组)和茶多酚治疗组(MPTP + TP组),每组4只。正常对照组不进行任何处理;茶多酚对照组灌胃给予茶多酚80 d;PD模型组静脉注射MPTP诱导PD模型,茶多酚治疗组在PD模型建立后给予茶多酚治疗80 d,每周2次用帕金森病临床行为评价量表评价各组动物运动损伤。实验动物经安乐死后,分离脑组织,高效液相色谱分析纹状体多巴胺及其代谢产物含量,免疫组织化学和体视学分析黑质多巴胺能神经元变化。结果 TP能减少MPTP诱导的食蟹猴黑质多巴胺能神经元的损伤并缓解其运动障碍。结果 首次在灵长类动物体内实验证实茶多酚能有效减少多巴胺能神经元的损伤并改善其运动机能。     

天宁寺社区高龄老人卫生服务需求调查分析

目的了解广外天宁寺社区高龄老人的健康状况和卫生服务需求,为有针对性地开展社区卫生服务提供依据。方法采取整群抽样调查方法,随机抽取天宁寺社区80岁以上高龄老人130人进行调查。调查内容涉及高龄老人的健康状况、卫生服务需求、护理照料需求、医疗保健需求及相关背景资料等内容。结果慢性病是高龄老人的主要卫生问题,医疗护理照料需求量增大。结论高龄老人是身体衰老、高概率带病生存的健康弱势群体,社区卫生服务要加强服务功能和形式的转变,为高龄老人提供医疗和护理照料为主的卫生服务,以提高老年人生活质量,保障社会家庭稳定。     

多状态Markov模型在社区老年人轻度认知损害转归分析中的应用

目的 利用多状态Markov模型对社区老年人轻度认知损害(MCI)转归进行研究.方法 通过MCI患者智商(IQ)变化反映随访人群认知功能的变化趋势,构建一个四状态模型,采用多状态Markov模型进行分析.结果 600例MCI患者中,男性174例(29.0%),女性426例(71.0%),年龄65～90岁,平均(69.7±6.6)岁.单因素分析显示,性别、年龄、文化程度、婚姻状况、吸烟、经济收入、脑溢血、高血压、高胆固醇、糖尿病、低密度脂蛋白胆固醇(LDL-C)水平、收缩压(SBP)、舒张压(DBP)等因素与认知功能有关.多因素分析显示,女性、高年龄、发生脑溢血及高SBP为认知稳定转化为认知重度恶化的危险因素(系数分别为0.762、0.366、0.885、0.069);高年龄是认知稳定转化为认知轻度恶化的危险因素(系数为0.038);高文化程度均为保护因素(系数分别为-0.219和-0.297).转移强度结果显示认知功能稳定进一步恶化(轻度+重度)的进度是好转的1.2倍;轻度恶化到认知功能稳定的进展强度是进一步发展成重度恶化的11.4倍多.结论 多状态Markov模型是处理纵向资料的有效工具.

Abstract：

Objective To introduce the Multi-state Markov model in studying the outcome prediction of mild cognitive impairment (MCI). Methods Based on the intelligence quotient (IQ)changes that reflecting the trends in cognitive function in the patients under follow-up program, we constructed a four states model and used Multi-state Markov model to analyze the patients. Results Among 600 MCI patients, there were 174(29.0%) males and 426(71.0%) females, with age range of 65-90 years-old (average 69.7±6.6). For univariate analysis, gender, age, education level, marital status, smoking, household income, cerebral hemorrhage, hypertension, high cholesterol, diabetes,LDL-C, SBP and DBP were found to be associated with cognitive function. For multivariate analysis,female, older age, cerebral hemorrhage and higher SBP were shown to be the risk factors for transition from the state of cognitive stability to the state of severe deterioration, and their coefficients were 0.762,0.366,0.885, and 0.069, respectively. Age (0.038) could influence the transition from the state of cognitive stability to slight deterioration. Higher education level was shown to be the protective factor for these transitions (-0.219 and-0.297). Transition intensity from the state of cognitive stability to the state of slight and severe deterioration was 1.2 times that of transition to the state of improving. Transition intensity from state of slight deterioration to cognitive stability was 11.4times that of transition to severe deterioration. Conclusion Multi-state Markov model was an effective tool in dealing with longitudinal data.