1. Introduction Diabetes is one of the four major chronic diseases with the greatest threat to human health. In its later stage, it often combines with vascular and neuropathy, involving multiple organs such as heart, brain, kidney, peripheral nerve, eyes and feet, which brings certain social and economic pressure to patients [1,2]. Diabetic foot (DF) is not only the second most expensive complication for diabetic patients, but also the main reason for amputation[3]. The incidence of diabetic foot in the late stage of diabetes mellitus patients over 50 years old in China is as high as 8.1%[4]. Epidemiological data show that 9.1 to 26.1 million diabetic patients suffer from foot ulcer every year in the world, with a global prevalence of 6.3% [5]. In recent years, the view that there is abnormal immune regulation in type 2 diabetic patients has been emerging, and it has been found that there is obvious abnormal T cell subsets in type 2 diabetic patients, suggesting that the cellular immune function may be disordered [6,7]. In order to provide reference for clinical diagnosis and treatment, this study aims to investigate the relationship between the level of cellular immunity and diabetic foot by observing the serum levels of healthy people, type 2 diabetic patients and type 2 diabetic foot patients. 2. Data and methods 2.1 Clinical data From January 2017 to November 2019, patients with type 2 diabetes mellitus, type 2 diabetes mellitus complicated with diabetic foot and healthy physical examination at the same period were selected from the Department of vascular surgery and endocrinology of Shanghai University of traditional Chinese medicine. Excluding the missing data, 152 cases were included, including 38 cases of type 2 diabetes mellitus, 38 cases of type 2 diabetes mellitus with diabetic foot and 76 cases of health examination. 2.2 Diagnostic criteria The diagnostic standard of diabetes mellitus refers to the diagnostic standard in Chinese diabetes prevention and control guide 2017 edition [8]: fasting blood glucose≥7.0mmol/l; plasma glucose≥ 11.1mmol/l at any time; blood glucose≥11.1mmol/l at 2h after glucose load. Diagnostic standard of diabetic foot diagnostic standard of diabetic foot refer to Chinese guidelines for diagnosis and treatment of diabetic foot (2017 Diagnostic criteria in [9]: diagnosis basis of diabetic lower extremity angiopathy: (1) in line with the diagnosis of diabetes; (2) with clinical manifestations of lower extremity ischemia; (3) auxiliary detection suggests lower extremity angiopathy. ABI ＜ 0.9 at rest, or ABI ＞ 0.9 at rest, but there are symptoms of lower extremity discomfort during exercise. After treadmill test, ABI is reduced by 15% ～ 20% or imaging suggests that lower extremity exists in blood vessels. The diagnosis of diabetic peripheral neuropathy was based on: (1) abnormal temperature perception; (2) hypoesthesia or disappearance of foot by nylon wire examination; (3) abnormal vibration perception; (4) disappearance of ankle reflex; (5) two or more items of nerve conduction velocity decreased. 2 or more of the above 5 tests can be diagnosed. 2.3 Inclusion and exclusion criteria Inclusion criteria: meet the diagnostic criteria; age ＞ 18; volunteer to participate in the study and sign the informed consent. Exclusion criteria: inconformity with inclusion criteria; type I diabetes mellitus; autoimmune disease; immunosuppressant taken within 3 months before blood sampling; serious cardiovascular, liver, kidney and nervous system diseases and psychosis, tumor patients; pregnant and lactating women. 2.4 Data collection The subjects collected basic information after admission, including patients' gender, age, course of diabetes. Blood samples were collected on an empty stomach in the morning of the next day to detect the level of glucose metabolism (including fasting blood glucose, 2-hour postprandial blood glucose, glycosylated hemoglobin), cellular immune indexes, etc. All blood tests were carried out by the laboratory of Shuguang Hospital Affiliated to Shanghai University of traditional Chinese medicine. 2.5 Statistical analysis All data are processed by statistical software SPSS 21.0, normal test and normal distribution of measurement data bank Data in (±s); non normal distribution data is represented by (median, interquartile distance), the difference between groups is compared, and the t-test is used for the group comparison when it is consistent with the normality and the variance is homogeneous; the rank sum test is used for the group comparison when it is not subject to the normal distribution; the chi square test is used for the count data; the rank sum test is used for the level data, and the binary logistic regression model is used for the analysis of the impact Factors, P ＜ 0.05 showed statistical difference. 3. Results 3.1 Clinical data As shown in Table 1, there was no significant difference in gender and age between the observation group and the control group (P ＞ 0.05); there was significant difference in glycosylated hemoglobin and fasting blood glucose between the two groups (P ＜ 0.001). As shown in Table 2, there was no statistical difference in fasting blood glucose, 2-hour postprandial blood glucose and glycosylated hemoglobin between the two subgroups of the observation group (P ＞ 0.05); there was statistical difference in age and diabetes duration between the two subgroups (P ＜ 0.05). 3.2 Comparison of cellular immunity As shown in Table 3, there was statistical difference in CD8 between the observation group and the control group (P ＜ 0.05), in CD25 and CD28 (P ＜ 0.01); there was no statistical difference in CD3, CD4, CD2, CD19, CD38, CD3 / HLA-DR and CD56 + 16nk between the two groups (P ＞ 0.05). There were significant differences in CD2, CD25, CD8 and CD28 between the two subgroups of the observation group (P ＜ 0.05), but no significant differences in CD3, CD4, CD19, CD38, CD3 / HLA-DR and CD56 + 16NK (P ＞ 0.05). Table 1 Comparison of basic data between the two groups (median, interquartile distance)Group Male / female / case Age (years) Fasting blood glucose (mmol / L) HbA1c(%)Observation group 53/23 70(64.25,77) 8.5(7.03,9.70) 8.25(6.9,9.36)control group 46/30 72(62,72) 5.2(5.1,5.2) 5.8(5.3,5.8)X2/Z/t 1.419 -1.774 12.89 9.81 P 0.233 0.076 ＜0.001 ＜0.001 Table 2 Comparison of basic data of patients in observation group (median, interquartile distance)Group Male / female / case Age (years) Course of diabetes (years) Fasting blood glucose (mmol / L) Blood glucose 2 hours after meal (mmol / L) HbA1c(%)DM+DF group 26/12 72.16(50,86) 16(10,20) 8.69(7.38,10.05) 15.34(8.98,17.62) 8.25(6.60,9.54)DM group 27/11 67.84(47,88) 10(5.75,10.25) 8.35(6.85,9.48) 13.37(9.5,16.36) 8.11(6.85,8.81)X2/Z 0.062 -2.219 -2.596 -1.237 -1.465 -0.140 P 0.803 0.027 0.009 0.216 0.143 0.888 Table 3 Comparison of serum cellular immune level in each group (median, interquartile distance)Note: compared with the control group,*P ＜ 0.05.*P ＜ 0.001; compared with the two subgroups,#P＜0.05.##P＜0.001Group CD3 CD4 CD2 CD8 CD19 Observation group 64.2(57.33,69.9) 39.95(35.3,44.93) 81.25(77.55,87.2) 29.40(24.25,34.98) 9.1(5.38,13.48)control group 60.3(59.4,73.8) 39.9(35.8,47.23) 81.2(77.3,85.8) 25.5(23,33.2)* 10.15(5.19,12.68)DM+DF group 65.05(58.43,70.35) 40.65(35.53,47.75) 83.85(78.83,88.5) 32.925(26.8,36.93) 8.38(5.20,13.25)DM group 63.65(55.7,68.93) 38.9(34.18,44.03) 80(74.4,84.25)# 25.8(22.76,29.80) # 10.02(5.45,14.10)Group CD25 CD38 CD3/HLA-DR CD56+16NK CD28 Observation group 4.65(2.68,6.05) 2.8(1.7,4.2) 11.4(6.73,16.2) 15(10.13,23.33) 22.55(18.23,26.80)control group 2.5(1.6,3.18)** 2.7(1.93,3.7) 12.2(7.88,16.9) 16.7(10,24.4) 13.4(8.8,21.9)**DM+DF group 5.67(3.63,6.43) 2.8(1.93,4.2) 11.2(6.1,15.13) 15.4(9.8,22.45) 25.34(21.32,28.36)DM group 3.75(2.01,5.60)# 2.8(1.28,2.8) 12(7.25,17.83) 14.5(10.75,23.68) 19.5(15.65,25.45)# Table 4 logistic regression analysis of influencing factors of diabetic footFactor B Wald OR 95%CI P CD2 -0.072 3.086 0.930 0.858,1.008 0.079 CD8 -0.084 4.358 0.920 0.850,0.995 0.037 CD25 -0.269 6.281 0.764 0.619,0.943 0.012 CD28 -0.074 2.576 0.929 0.848,1.016 0.108 3.3 Risk factors of diabetic foot The effect of CD2, CD8, CD25 and CD28 on diabetic foot was evaluated by binary logistic regression. Finally, the obtained logistic model is statistically significant, which can correctly classify 71.1% of the subjects. CD8, CD25 were statistically significant (P ＜ 0.05), CD28, CD2 were not statistically significant (P ＞ 0.05), CD8 [or95% CI 0.920 (0.850, 0.995)], CD25 [or95% CI 0.764 (0.619, 0.943) were independent influencing factors of diabetic foot. 4. Discussion Diabetic foot is a common complication in the later stage of diabetic patients. about 15% ～ 25% of diabetic patients will be complicated with diabetic foot in the later stage. Diabetic foot ulcer (DFU) is more common in the later stage of diabetic foot, which is often hard to heal [10]. once diabetic foot occurs, it will bring great economic and social burden to patients [11]. According to the relevant research, the medical expenses in the United States for diabetic foot related treatment plan cost up to 18.7 billion US dollars, and the hospitalization expenses for diabetic foot ulcer treatment up to 1.4 billion US dollars [12, 13]. The cost of diabetic foot treatment in South Korea increased from 296 million dollars in 2011 to 441 million dollars in 2016, indicating a significant increase in South Korea's investment in diabetic foot treatment [14]. In a survey on the cost of diabetic foot patients in New Zealand, it was found that the total cost of a diabetic foot rupture can reach more than 10000 US dollars [15]. The average hospitalization cost of diabetic foot patients in China is about 15000 yuan [16]. In addition, diabetic foot is also the main cause of non-traumatic amputation [17]. Diabetic foot accounts for 40% ～ 60% of all non-traumatic low amputation operations [18]. Therefore, if the early intervention can reduce the risk of diabetic foot, it can effectively avoid high medical costs, amputation and even death for diabetic patients. In recent years, the view that type 2 diabetes may also be an autoimmune disease and the occurrence of diabetic foot may be related to immunity has gradually arisen [19]. It was found that the C-reactive protein was negatively correlated with CD3 +, CD3 + CD4 +, CD3 + CD4 + / D3 + CD8 + and positively correlated with CD3 + CD8 + in diabetic patients with infection, and it was speculated that there was inflammatory reaction in diabetic patients with infection, which also affected the activation of T cells and the activation of T suppressor cells [20]. Li Haiyan[21] found that the levels of CD3 + cells, CD4 + cells and CD4 + / CD8 + cells in patients with diabetic foot complicated with deep infection were lower than those in patients with shallow infection, suggesting that the immune function of patients with diabetic foot infection was related to pathogenic bacteria and infection degree. Zhang lanrong [22] found that diabetic foot is closely related to immune factors such as IgM, IgG, C3 and C4. Jiang chunhuan [23] observed 20 diabetic foot patients and found that the serum IgG, IgM, IgE and IgA of diabetic foot patients were significantly higher than those of normal people, suggesting that there were blood and immunological abnormalities in type 2 diabetic foot patients. Li Fei et al [24] pointed out that diabetic foot ulcer is not only closely related to blood vessels, nerves and other diseases, but also closely related to immune disorders of the body. Immune regulation may become a new direction of diabetic foot treatment. Therefore, this study is based on the cellular immune level in serum to observe whether there is any difference in immune level between healthy people and diabetic patients, and between diabetic patients and patients with diabetic foot. The results show that there are some differences between diabetic patients and diabetic patients in age and course of diabetes, suggesting that age and course of diabetes may be risk factors for diabetic patients complicated with diabetic foot, which is consistent with our previous research results [25]. It can be seen from the cellular immune level that compared with the healthy people, the level of CD8, CD25 and CD28 in diabetic patients increased. Compared with diabetic patients, the level of CD2, CD8, CD25 and CD28 in diabetic foot patients increased. From the analysis of risk factors, it can be seen that the above CD8 and CD25 indexes are independent influencing factors of diabetic foot, and are negatively correlated with the occurrence of diabetic foot. In conclusion, the levels of CD8 and CD25 in cellular immunity may be used to predict the risk of diabetic foot in patients with type 2 diabetes. The increase of CD8 and CD25 may be an independent risk factor for diabetic foot. There are some limitations in this study. only the cases of diabetic foot in diabetic patients are counted, and no specific pathological changes are classified. For example, whether there are vascular diseases and neuropathy, whether the above pathological changes are related to the level of cellular immunity in serum will be our next research direction. [1] Grant PJ, Cosentino F. The 2019 ESC Guidelines on diabetes, prediabetes, and cardiovascular diseases developed in collaboration with the EASD: New features and the ‘Ten Commandments’ of the 2019 Guidelines are discussed by Professor Peter J. Grant and Professor Francesco Cosentino, the Task Force chairmen. Eur Heart J 2019, 40: 3215-321. [2] Zhao HY, McClure NS, Johnson JA. A Longitudinal Study on the Association Between Diabetic Foot Disease and Health-Related Quality of Life in Adults With Type 2 Diabetes. Can J Diabetes 2019, DOI：10.1016/j.jcjd.2019.08.008. [3] O’Brien JA, Patrick AR, Caro JJ. Cost of managing complications resulting from type 2 diabetes mellitus in Canada. BMC Health Serv Res 2003.3:7. [4] Wang FJ. Interpretation of guidelines for the prevention and treatment of diabetic foot in China (2019 Edition). J Hebei Med Univ 2019,40 (11): 1241-1245 + 1250. [5] Shang P, Lu J, Jing Y, Tang S, Zhu D, Bi Y. Global epidemiology of diabetic foot ulceration: A systematic review and meta-analysis. Ann Med 2017;49:106e16. [6] Zhu YQ, Hu Y, Mao XM. Research progress of immune abnormalities in type 2 diabetes. Chinese J diabetes 2015,23 (09): 859-861. [7] Fu LL, Zhang XK. Observation of cellular immune status and T cell subsets in elderly patients with type 2 diabetes. Chinese J Gerontol 2011,31 (11): 2099-2100. [8] Diabetes branch of Chinese Medical Association. Guidelines for the prevention and treatment of type 2 diabetes in China (2017). J practical med 2018, 38 (4): 292-344. [9] Chen DW, Ran XW. Interpretation of the 2017 guidelines for the diagnosis and treatment of diabetic foot. Chinese J physicians 2017, 19 (12): 1765-1767. [10] Yan ZC. Progress in diagnosis and treatment of diabetic foot. J Chongqing Medical Univ 2017,42 (3): 263-267. [11] Alosaimi FD, Labani R, Almasoud N. Associations of foot ulceration with quality of life and psychosocial determinants among patients with diabetes; a case-control study. J Foot Ankle Res 2019, 12: 57. [12] Nussbaum SR, Carter MJ, Fife CE. An Economic evaluation of the Impact, Cost, and Medicare Policy Implications of Chronic Nonhealing. Wounds.Value Health 2018, 21: 27-32. [13] Hicks CW, Canner JK, Karagozlu H. Contribution of 30-day readmissions to the increasing costs of care for the diabetic foot. J Vasc Surg 2019, 70(4): 1263-1270. [14] Chun D, Kim SY, Kim J. Epidemiology and Burden of Diabetic Foot Ulcer and Peripheral Arterial Disease in Korea. J Clin Med 2019,8: 748. [15] Joret MO, Osman K, Dean A. Multidisciplinary clinics reduce treatment costs and improve patient outcomes in diabetic foot disease. J Vasc Surg 2019, 70(3): 806-814. [16] Ding Q, Xu TD. Clinical characteristics of diabetic foot patients and analysis of hospitalization cost of medical treatment. New world of diabetes 2019,22 (05): 11-14 + 18. [17] Mathers CD, LoncarD. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006, 3 (11) :2012-2030. [18] Gu YQ. Guidelines for the diagnosis and treatment of diabetic foot in China. Chinese J clinicians 2020,48 (01): 19-27. [19] Wu BL, Tang QL. Research progress on the relationship between immunity and type 2 diabetes mellitus and diabetic foot. Youjiang med 2015,43 (01): 88-92. [20] Huang Y. Analysis of cellular immune function in patients with type 2 diabetes mellitus complicated with infection. J Qiqihar Med Coll 2014,35 (22): 3312-3313. [21] Li HY, Shan GL, Huang SC. Study on the relationship between infection characteristics of diabetic foot patients and lower extremity angiopathy and immune function. Chinese J hospital infection 2019,29 (04): 574-577 + 581. [22] Zhang LR, Wei DL, Zhou YY. Study on the correlation between TCM Syndromes of diabetic foot and coagulation and immune factors. World J TCM 2014,9 (8): 1017-1019. [23] Jiang CH. Detection of Hematology and immunology indexes in patients with type 2 diabetic foot. Chinese community physician 2013,15 (09): 271. [24] Li F, Xu Q, Zhu CJ, Zhang ZH. Research ideas of microenvironment and neurovascular immunity of diabetic foot ulcer and research progress of TCM Intervention. World J Integrated Chinese and Western med 2018,13 (08): 1181-1184. [25] Huang RY, Wang L, Zhang YF. Relationship between serum vitamin level and diabetes mellitus and diabetic foot. J Hainan Med Coll 2019,25 (16): 1227-1231. 1. IntroductionDiabetes is one of the four major chronic diseases with the greatest threat to human health. In its later stage, it often combines with vascular and neuropathy, involving multiple organs such as heart, brain, kidney, peripheral nerve, eyes and feet, which brings certain social and economic pressure to patients [1,2]. Diabetic foot (DF) is not only the second most expensive complication for diabetic patients, but also the main reason for amputation[3]. The incidence of diabetic foot in the late stage of diabetes mellitus patients over 50 years old in China is as high as 8.1%[4]. Epidemiological data show that 9.1 to 26.1 million diabetic patients suffer from foot ulcer every year in the world, with a global prevalence of 6.3% [5]. In recent years, the view that there is abnormal immune regulation in type 2 diabetic patients has been emerging, and it has been found that there is obvious abnormal T cell subsets in type 2 diabetic patients, suggesting that the cellular immune function may be disordered [6,7]. In order to provide reference for clinical diagnosis and treatment, this study aims to investigate the relationship between the level of cellular immunity and diabetic foot by observing the serum levels of healthy people, type 2 diabetic patients and type 2 diabetic foot patients.2. Data and methods2.1 Clinical dataFrom January 2017 to November 2019, patients with type 2 diabetes mellitus, type 2 diabetes mellitus complicated with diabetic foot and healthy physical examination at the same period were selected from the Department of vascular surgery and endocrinology of Shanghai University of traditional Chinese medicine. Excluding the missing data, 152 cases were included, including 38 cases of type 2 diabetes mellitus, 38 cases of type 2 diabetes mellitus with diabetic foot and 76 cases of health examination.2.2 Diagnostic criteriaThe diagnostic standard of diabetes mellitus refers to the diagnostic standard in Chinese diabetes prevention and control guide 2017 edition [8]: fasting blood glucose≥7.0mmol/l; plasma glucose≥ 11.1mmol/l at any time; blood glucose≥11.1mmol/l at 2h after glucose load.Diagnostic standard of diabetic foot diagnostic standard of diabetic foot refer to Chinese guidelines for diagnosis and treatment of diabetic foot (2017 Diagnostic criteria in [9]: diagnosis basis of diabetic lower extremity angiopathy: (1) in line with the diagnosis of diabetes; (2) with clinical manifestations of lower extremity ischemia; (3) auxiliary detection suggests lower extremity angiopathy. ABI ＜ 0.9 at rest, or ABI ＞ 0.9 at rest, but there are symptoms of lower extremity discomfort during exercise. After treadmill test, ABI is reduced by 15% ～ 20% or imaging suggests that lower extremity exists in blood vessels. The diagnosis of diabetic peripheral neuropathy was based on: (1) abnormal temperature perception; (2) hypoesthesia or disappearance of foot by nylon wire examination; (3) abnormal vibration perception; (4) disappearance of ankle reflex; (5) two or more items of nerve conduction velocity decreased. 2 or more of the above 5 tests can be diagnosed.2.3 Inclusion and exclusion criteriaInclusion criteria: meet the diagnostic criteria; age ＞ 18; volunteer to participate in the study and sign the informed consent.Exclusion criteria: inconformity with inclusion criteria; type I diabetes mellitus; autoimmune disease; immunosuppressant taken within 3 months before blood sampling; serious cardiovascular, liver, kidney and nervous system diseases and psychosis, tumor patients; pregnant and lactating women.2.4 Data collectionThe subjects collected basic information after admission, including patients' gender, age, course of diabetes. Blood samples were collected on an empty stomach in the morning of the next day to detect the level of glucose metabolism (including fasting blood glucose, 2-hour postprandial blood glucose, glycosylated hemoglobin), cellular immune indexes, etc. All blood tests were carried out by the laboratory of Shuguang Hospital Affiliated to Shanghai University of traditional Chinese medicine.2.5 Statistical analysisAll data are processed by statistical software SPSS 21.0, normal test and normal distribution of measurement data bank Data in (±s); non normal distribution data is represented by (median, interquartile distance), the difference between groups is compared, and the t-test is used for the group comparison when it is consistent with the normality and the variance is homogeneous; the rank sum test is used for the group comparison when it is not subject to the normal distribution; the chi square test is used for the count data; the rank sum test is used for the level data, and the binary logistic regression model is used for the analysis of the impact Factors, P ＜ 0.05 showed statistical difference.3. Results3.1 Clinical dataAs shown in Table 1, there was no significant difference in gender and age between the observation group and the control group (P ＞ 0.05); there was significant difference in glycosylated hemoglobin and fasting blood glucose between the two groups (P ＜ 0.001). As shown in Table 2, there was no statistical difference in fasting blood glucose, 2-hour postprandial blood glucose and glycosylated hemoglobin between the two subgroups of the observation group (P ＞ 0.05); there was statistical difference in age and diabetes duration between the two subgroups (P ＜ 0.05).3.2 Comparison of cellular immunityAs shown in Table 3, there was statistical difference in CD8 between the observation group and the control group (P ＜ 0.05), in CD25 and CD28 (P ＜ 0.01); there was no statistical difference in CD3, CD4, CD2, CD19, CD38, CD3 / HLA-DR and CD56 + 16nk between the two groups (P ＞ 0.05). There were significant differences in CD2, CD25, CD8 and CD28 between the two subgroups of the observation group (P ＜ 0.05), but no significant differences in CD3, CD4, CD19, CD38, CD3 / HLA-DR and CD56 + 16NK (P ＞ 0.05).Table 1 Comparison of basic data between the two groups (median, interquartile distance)Group Male / female / case Age (years) Fasting blood glucose (mmol / L) HbA1c(%)Observation group 53/23 70(64.25,77) 8.5(7.03,9.70) 8.25(6.9,9.36)control group 46/30 72(62,72) 5.2(5.1,5.2) 5.8(5.3,5.8)X2/Z/t 1.419 -1.774 12.89 9.81 P 0.233 0.076 ＜0.001 ＜0.001Table 2 Comparison of basic data of patients in observation group (median, interquartile distance)Group Male / female / case Age (years) Course of diabetes (years) Fasting blood glucose (mmol / L) Blood glucose 2 hours after meal (mmol / L) HbA1c(%)DM+DF group 26/12 72.16(50,86) 16(10,20) 8.69(7.38,10.05) 15.34(8.98,17.62) 8.25(6.60,9.54)DM group 27/11 67.84(47,88) 10(5.75,10.25) 8.35(6.85,9.48) 13.37(9.5,16.36) 8.11(6.85,8.81)X2/Z 0.062 -2.219 -2.596 -1.237 -1.465 -0.140 P 0.803 0.027 0.009 0.216 0.143 0.888Table 3 Comparison of serum cellular immune level in each group (median, interquartile distance)Note: compared with the control group,*P ＜ 0.05.*P ＜ 0.001; compared with the two subgroups,#P＜0.05.##P＜0.001Group CD3 CD4 CD2 CD8 CD19 Observation group 64.2(57.33,69.9) 39.95(35.3,44.93) 81.25(77.55,87.2) 29.40(24.25,34.98) 9.1(5.38,13.48)control group 60.3(59.4,73.8) 39.9(35.8,47.23) 81.2(77.3,85.8) 25.5(23,33.2)* 10.15(5.19,12.68)DM+DF group 65.05(58.43,70.35) 40.65(35.53,47.75) 83.85(78.83,88.5) 32.925(26.8,36.93) 8.38(5.20,13.25)DM group 63.65(55.7,68.93) 38.9(34.18,44.03) 80(74.4,84.25)# 25.8(22.76,29.80) # 10.02(5.45,14.10)Group CD25 CD38 CD3/HLA-DR CD56+16NK CD28 Observation group 4.65(2.68,6.05) 2.8(1.7,4.2) 11.4(6.73,16.2) 15(10.13,23.33) 22.55(18.23,26.80)control group 2.5(1.6,3.18)** 2.7(1.93,3.7) 12.2(7.88,16.9) 16.7(10,24.4) 13.4(8.8,21.9)**DM+DF group 5.67(3.63,6.43) 2.8(1.93,4.2) 11.2(6.1,15.13) 15.4(9.8,22.45) 25.34(21.32,28.36)DM group 3.75(2.01,5.60)# 2.8(1.28,2.8) 12(7.25,17.83) 14.5(10.75,23.68) 19.5(15.65,25.45)#Table 4 logistic regression analysis of influencing factors of diabetic footFactor B Wald OR 95%CI P CD2 -0.072 3.086 0.930 0.858,1.008 0.079 CD8 -0.084 4.358 0.920 0.850,0.995 0.037 CD25 -0.269 6.281 0.764 0.619,0.943 0.012 CD28 -0.074 2.576 0.929 0.848,1.016 0.1083.3 Risk factors of diabetic footThe effect of CD2, CD8, CD25 and CD28 on diabetic foot was evaluated by binary logistic regression. Finally, the obtained logistic model is statistically significant, which can correctly classify 71.1% of the subjects. CD8, CD25 were statistically significant (P ＜ 0.05), CD28, CD2 were not statistically significant (P ＞ 0.05), CD8 [or95% CI 0.920 (0.850, 0.995)], CD25 [or95% CI 0.764 (0.619, 0.943) were independent influencing factors of diabetic foot.4. DiscussionDiabetic foot is a common complication in the later stage of diabetic patients. about 15% ～ 25% of diabetic patients will be complicated with diabetic foot in the later stage. Diabetic foot ulcer (DFU) is more common in the later stage of diabetic foot, which is often hard to heal [10]. once diabetic foot occurs, it will bring great economic and social burden to patients [11]. According to the relevant research, the medical expenses in the United States for diabetic foot related treatment plan cost up to 18.7 billion US dollars, and the hospitalization expenses for diabetic foot ulcer treatment up to 1.4 billion US dollars [12, 13]. The cost of diabetic foot treatment in South Korea increased from 296 million dollars in 2011 to 441 million dollars in 2016, indicating a significant increase in South Korea's investment in diabetic foot treatment [14]. In a survey on the cost of diabetic foot patients in New Zealand, it was found that the total cost of a diabetic foot rupture can reach more than 10000 US dollars [15]. The average hospitalization cost of diabetic foot patients in China is about 15000 yuan [16]. In addition, diabetic foot is also the main cause of non-traumatic amputation [17]. Diabetic foot accounts for 40% ～ 60% of all non-traumatic low amputation operations [18]. Therefore, if the early intervention can reduce the risk of diabetic foot, it can effectively avoid high medical costs, amputation and even death for diabetic patients.In recent years, the view that type 2 diabetes may also be an autoimmune disease and the occurrence of diabetic foot may be related to immunity has gradually arisen [19]. It was found that the C-reactive protein was negatively correlated with CD3 +, CD3 + CD4 +, CD3 + CD4 + / D3 + CD8 + and positively correlated with CD3 + CD8 + in diabetic patients with infection, and it was speculated that there was inflammatory reaction in diabetic patients with infection, which also affected the activation of T cells and the activation of T suppressor cells [20]. Li Haiyan[21] found that the levels of CD3 + cells, CD4 + cells and CD4 + / CD8 + cells in patients with diabetic foot complicated with deep infection were lower than those in patients with shallow infection, suggesting that the immune function of patients with diabetic foot infection was related to pathogenic bacteria and infection degree. Zhang lanrong [22] found that diabetic foot is closely related to immune factors such as IgM, IgG, C3 and C4. Jiang chunhuan [23] observed 20 diabetic foot patients and found that the serum IgG, IgM, IgE and IgA of diabetic foot patients were significantly higher than those of normal people, suggesting that there were blood and immunological abnormalities in type 2 diabetic foot patients. Li Fei et al [24] pointed out that diabetic foot ulcer is not only closely related to blood vessels, nerves and other diseases, but also closely related to immune disorders of the body. Immune regulation may become a new direction of diabetic foot treatment. Therefore, this study is based on the cellular immune level in serum to observe whether there is any difference in immune level between healthy people and diabetic patients, and between diabetic patients and patients with diabetic foot.The results show that there are some differences between diabetic patients and diabetic patients in age and course of diabetes, suggesting that age and course of diabetes may be risk factors for diabetic patients complicated with diabetic foot, which is consistent with our previous research results [25]. It can be seen from the cellular immune level that compared with the healthy people, the level of CD8, CD25 and CD28 in diabetic patients increased. Compared with diabetic patients, the level of CD2, CD8, CD25 and CD28 in diabetic foot patients increased. From the analysis of risk factors, it can be seen that the above CD8 and CD25 indexes are independent influencing factors of diabetic foot, and are negatively correlated with the occurrence of diabetic foot.In conclusion, the levels of CD8 and CD25 in cellular immunity may be used to predict the risk of diabetic foot in patients with type 2 diabetes. The increase of CD8 and CD25 may be an independent risk factor for diabetic foot. There are some limitations in this study. only the cases of diabetic foot in diabetic patients are counted, and no specific pathological changes are classified. For example, whether there are vascular diseases and neuropathy, whether the above pathological changes are related to the level of cellular immunity in serum will be our next research direction.References[1] Grant PJ, Cosentino F. 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