高脂血症合并高体重指数或心血管相关疾病患者的中医证型研究

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1、提要目的：本文在中医辨证论治的基础上，结合临床诊断方法，将收集的高脂血症患者进行中医证型分类，并运用现代统计学方法将合并高体重指数（BMI）或心血管相关疾病患者的中医证型进行分析，了解高脂血症合并高BMI或心血管相关病患者的中医证型分布，对于疾病的预防、诊断与治疗起着极大的作用。方法：收集120例高脂血症患者，记录他们的姓名、性别、年龄、身高、体重、心血管相关病、血脂指标等项目。将他们分为痰湿阻遏型、脾肾阳虚型、肝肾阴虚型、阴虚阳亢型及气滞血瘀型，把合并有高BMI或心血管相关疾病患者所属的中医证型进行分析。结果：①高脂血症患者为气滞血瘀及痰湿阻遏型的可能性大。②患者的性别的中医

2、证型分布经统计学比较无显著性差异（P>0.05）。③高脂血症患者的年龄与其中医证型分布有统计学意义，老年人患高脂血症的可能性较大。④BMI方面，合并高BMI的患者为痰湿阻遏型可能性较高。⑤合并心血管相关疾病方面，合并冠心病患者为气滞血瘀型的几率较大，合并糖尿病患者为肝肾阴虚型的几率较大，其次为痰湿阻遏型。结论：高脂血症合并高BMI或心血管相关疾病患者的中医证型分布存在着一定的规律性。关键词高脂血症；体重指数；心血管相关疾病；中医证型ResearchoftheSyndromeTypesofTraditionalChineseMedicineintheHyperlipidemiaP

3、eopleWhoHaveExorbitantBMIorIncorporativeCardiovascularDiseasesSpeciality:CardiologyofTCMAuthor:OuHaiyanTutor:Pro.WangYingAbstractObjective:InthispaperIdividethehyperlipidemiapeopleintofivegroupsonthebaseofthesyndromedifferentiationsofTCMandclinicaldiagnosismethod,andthenanalyzethesyndrometyp

4、esoftraditionalChineseMedicineofthehyperlipidemiapeoplewhohaveexorbitantBMIorincorporativeCardiovasculardiseaseswiththemethodofmodernstatistics.TheresultofthedistributionofthehyperlipidemiapeoplewhohaveexorbitantBMIorincorporativeCardiovasculardiseasesisveryimportantinpreventing,diagnosingan

5、dcuringthedisease.Method:Firstly,Icollectonehundredandtwentypatients,writedowntheirnames,genders,ages,heights,weights,incorporativeCardiovasculardiseasesandbloodlipidindex.Secondly,Idividethepatientsintofivesyndrometypes:phlegm-stagnationsyndrome，spleen-kidney-yang-deficiencysyndrome,liver-k

6、idney-yin-deficiencysyndrome,yin-deficiency-yang-superfluitysyndrome,qiandblood-stagnationsyndrome.Thirdly,IanalyzethesyndrometypesoftraditionalChineseMedicineofthehyperlipidemiapeoplewhohaveexorbitantBMIorincorporativeCardiovasculardiseases,andthendiscusstheirrelationship.Result：Thepatients

7、aremorelikelytobeqiandblood-stagnationsyndromeandphlegm-stagnationsyndrome;thehyperlipidemiapeopleofdifferentsyndrometypesofTCMdon’thaveobviousdifferencesingenders;theelderpatientsmaybemorelikelytobehyperlipidemia;thepatientswhohaveexorbitantBMImay