OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatm...OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatments to different types. In this paper, we investigate how to properly carry out the classification for patients with VMCI aged 50 or above using a novel data-driven method known as latent tree analysis （LTA）. METHOD： A cross-sectional survey on VMCI was carried out in several regions in Northern China between February 2008 and February 2012 which resulted in a data set that involves 803 patients and 93 symptoms. LTA was performed on the data to reveal symptom co-occurrence patterns, and the patients were partitioned into clusters in multiple ways based on the patterns. The patient clusters were matched up with syndrome types, and population statistics of the clusters are used to quantify the syndrome types and to establish classification rules. RESULTS： Eight syndrome types are identified： Qi deficiency, Qi stagnation, Blood deficiency, Blood stasis, Phlegm-dampness, Fire-heat, Yang deficiency, and Yin deficiency. The prevalence and symptom occurrence characteristics of each syndrome type are determined. Quantitative classification rules are established for determining whether a patient belongs to each of the syndrome types. CONCLUSION： A solution for the TCM syndrome classification problem for patients with VMCI and aged 50 or above is established based on the LTA of unlabeled symptom survey data. The results can be used as a reference in clinic practice to improve the quality of syndrome differentiation and to reduce diagnosis variances across physicians. They can also be used for patient selection in research projects aimed at finding biomarkers for the syndrome types and in randomized control trials aimed at determining the efficacy of TCM treatments of VMCI.展开更多
目的：探讨血管性认知损害（vascular cognitive i mpairment,VCI）患者的认知功能与中医证候的相关性,为VCI的中医辨证治疗提供依据。方法：2006年12月~2010年3月从北京东直门医院老年病科和社区居民中招募774名患者,筛选出认知正常组...目的：探讨血管性认知损害（vascular cognitive i mpairment,VCI）患者的认知功能与中医证候的相关性,为VCI的中医辨证治疗提供依据。方法：2006年12月~2010年3月从北京东直门医院老年病科和社区居民中招募774名患者,筛选出认知正常组251例,VCI组107例。采用海金斯基缺血量表（Hachinski ischemic scale,HIS）、汉密尔顿抑郁评定量表（Hamilton depression scale,HAMD）、简易精神状态检查（mini-mental state examination,MMSE）中文版、临床痴呆评定量表（clinical dementia ratingscale,CDR）、画钟试验（clock drawing test,CDT）及日常生活能力量表（ability of dailyliving,ADL）评价患者认知功能、日常生活能力和痴呆的严重程度等,采用偏相关分析法分析VCI患者认知功能与中医证候的相关性。结果：VCI组中医证候与量表成绩的相关性分析显示,MMSE总分、CDT得分均与痰浊蒙窍证呈负相关（r=-0.525,r=-0.321;P=0.000,P=0.001）,ADL与痰浊蒙窍证呈正相关（r=0.424,P=0.000）,与肾精亏虚证呈正相关（r=0.216,P=0.028）。VCI组的认知功能与中医证候的偏相关分析显示,MMSE中总定向力以及时间和空间定向力得分均与痰浊蒙窍证呈负相关（r=-0.451,r=-0.448,r=-0.392;P=0.001,P=0.000,P=0.004）,单词即刻记忆和单词延迟回忆得分与痰浊蒙窍证呈负相关（r=-0.355,r=-0.225;P=0.000,P=0.021）,计算力/注意力、语言功能及执行功能得分均与痰浊蒙窍证呈负相关（r=-0.379,r=-0.448,r=-0.321;P=0.000,P=0.000,P=0.013）。痰浊蒙窍证患者的MMSE中总定向力、时间定向力、空间定向力、注意力/计算力均显著低于无痰浊蒙窍证患者（P〈0.01）,痰浊蒙窍证患者语言功能及单词延迟回忆得分均显著低于无痰浊蒙窍证患者（P〈0.05）。结论：VCI的主要中医证候为肾精亏虚、痰浊蒙窍和瘀阻脑络,其中痰浊与患者定向力、记忆力、注意力/计算力、语言功能关系密切,故化痰开窍法可用于防治血管性认知损害。展开更多
基金supported by the Hong Kong Research Grants Council under grant NO.16202515 and 16212516Guangzhou HKUST Fok Ying Tung Research Institute,China Ministry of Science and Technology TCM Special Research Projects Program under grant No.200807011,No.201007002 and No.201407001-8+2 种基金Beijing Science and Technology Program under grant No.Z111107056811040Beijing New Medical Discipline Development Program under grant No.XK100270569Project of Beijing University of Chinese Medicine under grant No.2011-CXTD-23
文摘OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatments to different types. In this paper, we investigate how to properly carry out the classification for patients with VMCI aged 50 or above using a novel data-driven method known as latent tree analysis （LTA）. METHOD： A cross-sectional survey on VMCI was carried out in several regions in Northern China between February 2008 and February 2012 which resulted in a data set that involves 803 patients and 93 symptoms. LTA was performed on the data to reveal symptom co-occurrence patterns, and the patients were partitioned into clusters in multiple ways based on the patterns. The patient clusters were matched up with syndrome types, and population statistics of the clusters are used to quantify the syndrome types and to establish classification rules. RESULTS： Eight syndrome types are identified： Qi deficiency, Qi stagnation, Blood deficiency, Blood stasis, Phlegm-dampness, Fire-heat, Yang deficiency, and Yin deficiency. The prevalence and symptom occurrence characteristics of each syndrome type are determined. Quantitative classification rules are established for determining whether a patient belongs to each of the syndrome types. CONCLUSION： A solution for the TCM syndrome classification problem for patients with VMCI and aged 50 or above is established based on the LTA of unlabeled symptom survey data. The results can be used as a reference in clinic practice to improve the quality of syndrome differentiation and to reduce diagnosis variances across physicians. They can also be used for patient selection in research projects aimed at finding biomarkers for the syndrome types and in randomized control trials aimed at determining the efficacy of TCM treatments of VMCI.
