本文選題：經(jīng)筋 + 結(jié)筋病灶點(diǎn)��； 參考：《遼寧中醫(yī)藥大學(xué)》2016年碩士論文

【摘要】：目的:采用數(shù)據(jù)挖掘方法分析膝骨性關(guān)節(jié)炎(KOA)患者下肢筋結(jié)點(diǎn)的分布規(guī)律和相互聯(lián)系,初步驗(yàn)證下肢結(jié)筋病灶點(diǎn)分布的循經(jīng)筋特異性,初步探索局部與遠(yuǎn)端筋結(jié)點(diǎn)之間的解剖關(guān)系,為經(jīng)筋針刺治療KOA臨床選點(diǎn)提供理論依據(jù)。材料與方法:對(duì)122例KOA患者單側(cè)下肢進(jìn)行筋結(jié)點(diǎn)觸診檢查,重點(diǎn)檢查并記錄患肢膝乆部的鶴頂次、髕下、髕內(nèi)下、髕外下、髕外、髕內(nèi)、脛骨外髁、脛骨內(nèi)髁、足三里次、成骨次、成腓間、陽陵次、腓骨小頭、毼毼次、膝關(guān)次、陰陵上、浮郄次、委中次、委陽次、陰谷次等局部筋結(jié)點(diǎn)觸發(fā)情況,以及髖臀部的承扶次、髂后上棘、環(huán)跳次,髖部的中空次、髀樞、健胯次,腹股溝處的氣沖次、陰廉次、中空次、五樞次,踝部的解溪次、昆侖次、女膝次、公孫上、照海次等遠(yuǎn)端筋結(jié)點(diǎn)觸發(fā)情況。采用Microsoft Excel軟件對(duì)觸診數(shù)據(jù)進(jìn)行處理,并導(dǎo)入SPSS Clementine 12.0軟件進(jìn)行數(shù)據(jù)挖掘處理,分析患者下肢筋結(jié)點(diǎn)的頻次和頻率,采用Apriori算法分析膝(乆)部周圍筋結(jié)點(diǎn)觸診結(jié)果的關(guān)聯(lián)規(guī)則,膝(乆)部周圍與遠(yuǎn)端筋結(jié)點(diǎn)觸診結(jié)果的關(guān)聯(lián)規(guī)則;并采用兩步聚類算法分析下肢筋結(jié)點(diǎn)觸診結(jié)果的聚類分組情況。結(jié)果:1.局部筋結(jié)點(diǎn)出現(xiàn)頻次和頻率由高到低依次為足陽明經(jīng)筋筋結(jié)點(diǎn)、足太陽經(jīng)筋筋結(jié)點(diǎn)、足少陽經(jīng)筋筋結(jié)點(diǎn)和足三陰經(jīng)筋筋結(jié)點(diǎn),遠(yuǎn)端筋結(jié)點(diǎn)出現(xiàn)頻次和頻率由高到低依次為足陽明經(jīng)筋筋結(jié)點(diǎn)、足少陽經(jīng)筋筋結(jié)點(diǎn)、足太陽經(jīng)筋筋結(jié)點(diǎn)和足三陰經(jīng)筋筋結(jié)點(diǎn)。2.關(guān)聯(lián)規(guī)則Apriori算法在最小支持度10%,最小置信度80%,提升大于1時(shí)確定膝(乆)部周圍兩點(diǎn)間筋結(jié)點(diǎn)出現(xiàn)頻率關(guān)聯(lián)規(guī)則14條,具有較大關(guān)聯(lián)的有髕內(nèi)下和鶴頂次(支持度52.46%,置信度87.50%)、委陽次和陰谷次(支持度37.70%,置信度86.96%)、髕內(nèi)下和髕外下(支持度52.46%,置信度85.94%)、髕內(nèi)下和髕內(nèi)(支持度71.31%,置信度85.06%)、委陽次與委中次(支持度58.20%,置信度84.51%)等。在最小支持度15%,最小置信度85%,提升大于1時(shí),確定膝(乆)部周圍3筋結(jié)點(diǎn)之間關(guān)聯(lián)規(guī)則45條,在最小支持度20%,最小置信度90%,提升大于1時(shí),確定4個(gè)及以上筋結(jié)點(diǎn)關(guān)聯(lián)規(guī)則39條。3.關(guān)聯(lián)規(guī)則Apriori算法在最小支持度10%,最小置信度60%,提升大于1時(shí)確定膝(乆)部周圍與臀、髖、腹股溝等部位2個(gè)筋結(jié)點(diǎn)之間關(guān)聯(lián)規(guī)則22條,置信度由高到低分別有承扶次和委中次(支持度58.2%,置信度81.69%)髂后上棘和委中次(支持度58.2%,置信度78.87%)承扶次和陰谷次(支持度37.7%,置信度76.09%)承扶次和委陽次(支持度63.93%,置信度74.36%)髂后上棘和委陽次(支持度63.93%,置信度74.36%)等。在最小支持度10%,最小置信度80%,提升大于1時(shí),確定三點(diǎn)內(nèi)關(guān)聯(lián)規(guī)則21條,在最小支持度15%,最小置信度90%,提升大于1時(shí),確定4個(gè)及以上筋結(jié)點(diǎn)關(guān)聯(lián)規(guī)則40條。4關(guān)聯(lián)規(guī)則Apriori算法在最小支持度5%,最小置信度55%,提升大于1時(shí)確定膝(乆)部周圍與踝關(guān)節(jié)部位2個(gè)筋結(jié)點(diǎn)之間關(guān)聯(lián)規(guī)則9條,置信度由高到低分別有公孫上和足三里次(支持度44.26%,置信度85.19%)女膝次和陰谷次(支持度37.7%,置信度78.26%)解溪次和髕下(支持度50%,置信度68.85%)解溪次和鶴頂次(支持度52.46%,置信度60.94%)女膝次和委陽次(支持度63.93%,置信度60.26%)等。在最小支持度10%,最小置信度80%,提升大于1時(shí),確定三點(diǎn)內(nèi)關(guān)聯(lián)規(guī)則28條,在最小支持度20%,最小置信度85%,提升大于1時(shí),確定4個(gè)及以上筋結(jié)點(diǎn)關(guān)聯(lián)規(guī)則41條。5采用兩步聚類分析將下肢筋結(jié)點(diǎn)出現(xiàn)情況在沒有先驗(yàn)知識(shí)的前提下分為了3組,各種筋結(jié)點(diǎn)所屬經(jīng)筋分布差異具有統(tǒng)計(jì)學(xué)意義(p0.05)。結(jié)論:1.KOA患者下肢筋結(jié)點(diǎn)出現(xiàn)的關(guān)聯(lián)規(guī)則與經(jīng)筋循行之間存在較強(qiáng)的聯(lián)系。2.KOA患者下肢筋結(jié)點(diǎn)出現(xiàn)的關(guān)聯(lián)規(guī)則與筋結(jié)點(diǎn)局部肌肉、韌帶等軟組織解剖結(jié)構(gòu)存在相關(guān)性。3.KOA患者下肢筋結(jié)點(diǎn)的聚類情況具有經(jīng)筋分布的特異性。
[Abstract]:Objective: to analyze the distribution and correlation of the lower limb tendons in patients with knee osteoarthritis (KOA) by data mining, and to preliminarily verify the meridian specificity of the distribution of the lesions of the lower extremities and preliminarily explore the anatomical relationship between the local and the distal tendons, and provide a theoretical basis for the clinical selection of KOA. Method: 122 cases of KOA patients with unilateral lower limb muscle touch examination, focus on the examination and record of the leg of the limb of the crane top, patellar, patellar, patellar, patellar, outside patellar, patellar, the tibial condyle, the tibial condyle, the three times of the bone, the fibula, Yang mausoleum, knee, Yin mausoleum, floating cleft times, Yin mausoleum, Yin mausoleum, Yin The triggering of the local gluten nodes of the valley, the buttocks and buttocks, the back of the iliac upper spine, the ring jump, the hip, the hip, the hip, the groin, the inferior, the hollow, the five pivot, the ankle, the Kunlun times, the grand sun, and the other distal tendons, are triggered by the Microsoft Excel software. The palpation data were processed, and the SPSS Clementine 12 software was introduced to data mining to analyze the frequency and frequency of the patients' lower limb tendon nodes. The association rules of the contact results of the tendon of the knee and the distal tendon nodes around the knee were analyzed by Apriori algorithm, and the two step clustering was used to calculate the association rules of the contact results between the knee and the distal tendon. Results: 1. the clustering and grouping of the results of palpation of the joints of the lower limbs were analyzed. Results: the frequency and frequency of the nodes of the local tendons from high to low were the joints of the foot Yang Ming meridian, the joints of the sun meridian tendons, the joints of the foot Shaoyang meridian and the foot of the foot of the foot of three yin meridians, and the frequency and frequency of the distal tendons from the high to the low in the order of the foot Yang Ming meridian. Tendons node, foot Shaoyang meridian node, foot sun tendons node and foot three yin meridian node.2. association rule Apriori algorithm in the minimum support 10%, the minimum confidence 80%, when the elevation is more than 1 to determine the two points of the knee between the two points of the knee joint frequency association rule 14, with a larger correlation of the patellar and crane top (52 support degree) .46%, confidence level 87.50%), committee Yang and Yin Valley Times (support 37.70%, confidence 86.96%), inferior patellar and outside of patellar (support 52.46%, confidence 85.94%), internal and internal patellar (71.31%, confidence 85.06%) in the patellar and patellar (support degree 58.20%, confidence 84.51%), and the minimum support degree 15%, minimum confidence 85%, promotion greater than 1. To determine the 45 association rules between the 3 tendon nodes around the knee, with the minimum support 20%, the minimum confidence 90% and the increase greater than 1, the Apriori algorithm of 39.3. association rules for the association rules of the 4 and above reinforcement nodes is determined by the minimum support 10%, the minimum confidence 60%, and the promotion of the hip, hip, groin and other parts around the knee. 22 association rules between the nodes of the tendon and the confidence degree from high to low, including bearing and supporting and central secondary (support 58.2%, confidence level 81.69%) of the posterior iliac spine and the central secondary (support 58.2%, confidence 78.87%) bearing support and Yin Valley (support degree 37.7%, confidence 76.09%) bearing and support times (support degree 63.93%, confidence 74.36%) and the posterior upper iliac spine (support degree 63.93%, confidence degree 74.36%) and the posterior upper iliac spine, respectively. When the minimum support degree (63.93%, confidence 74.36%), and so on. When the minimum support degree 10%, the minimum confidence 80%, and the lifting greater than 1, the association rule 21 in three points is determined. When the minimum support degree is 15%, the minimum confidence 90% is 90%, and the lifting is greater than 1, the Apriori algorithm of the association rule of the association rule of the.4 is minimum support 5% and minimum. The reliability is 55%, and when the elevation is greater than 1, a rule of 9 association rules between the knee and the ankle joints is determined. The confidence degree is from high to low, with high to low (support 44.26%, confidence 85.19%) in the knee and Yin Valley (support 37.7%, confidence 78.26%) and under patellar (support 50%, confidence 68.85%). Times and crane top times (support degree 52.46%, confidence 60.94%) female knee and committee Yang times (support degree 63.93%, confidence 60.26%), etc.. When minimum support 10%, minimum confidence 80%, and higher than 1, determine the Association Rule 28 in three, minimum support 20%, minimum confidence 85%, increase greater than 1, determine 4 and above association rule 41 association rules 41 A two step cluster analysis was used to divide the appearance of the tendons of the lower extremities into 3 groups without prior knowledge, and the differences in the distribution of the tendons of all kinds of tendons were statistically significant (P0.05). Conclusion: there is a strong association between the association rules of the appearance of the lower limb tendons in 1.KOA patients and the association between the meridians and the tendons of the.2.KOA patients. There is a correlation between the association rules and the local muscle, ligaments and other soft tissue structures of the tendons. The clustering of the lower limbs of the.3.KOA patients has the specificity of the tendons distribution.
【學(xué)位授予單位】：遼寧中醫(yī)藥大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：R246.9

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本文編號(hào)：2009405