PDF(Pubmed)
Abstract：
UNASSIGNED: To investigate the factors influencing accelerated aging in patients with type 2 diabetes mellitus (T2DM) and coronary heart disease (CHD).
UNASSIGNED: A total of 216 patients diagnosed with T2DM and CHD between August 2019 and August 2023 at Xuzhou Central Hospital were selected. Patients were divided into an aging group and a non-aging group, based on the positive or negative values of phenotypic age acceleration (PhenoAgeAccel). Logistic regression analysis was conducted. Variables that had a univariate analysis P< 0.05 were included in the multivariate analysis to identify factors influencing aging in patients with T2DM and CHD, and the area under the curve of the model was reported.
UNASSIGNED: This study included 216 patients, with 89 in the accelerated aging group, and 127 in the non-accelerated aging group. The average age of patients was 70.40 (95% CI: 69.10-71.69) years, with 137 males (63.4%). Compared with the non-accelerated aging group, patients in the accelerated aging group were older, with a higher proportion of males, and a higher prevalence of hypertension, stable angina pectoris, and unstable angina pectoris. Multivariate Logistic regression analysis indicated that the absolute value of neutrophils (NEUT#), urea (UREA), adenosine deaminase (ADA), and the triglyceride-glucose index (TyG) were risk factors for accelerated aging, while cholinesterase (CHE) was a protective factor. For each unit increase in NEUT#, UREA, ADA, and TyG, the risk of aging increased by 64%, 48%, 10%, and 789%, respectively. The overall area under the receiver operating characteristic (ROC) curve of the model in the training set was 0.894, with a 95% confidence interval (CI) of 0.851-0.938.
UNASSIGNED: NEUT#, CHE, UREA, ADA, and TyG are predictors of accelerated aging in patients with T2DM and CHD, with the model showing favorable overall predictive performance.
UNASSIGNED: A total of 216 patients diagnosed with T2DM and CHD between August 2019 and August 2023 at Xuzhou Central Hospital were selected. Patients were divided into an aging group and a non-aging group, based on the positive or negative values of phenotypic age acceleration (PhenoAgeAccel). Logistic regression analysis was conducted. Variables that had a univariate analysis P< 0.05 were included in the multivariate analysis to identify factors influencing aging in patients with T2DM and CHD, and the area under the curve of the model was reported.
UNASSIGNED: This study included 216 patients, with 89 in the accelerated aging group, and 127 in the non-accelerated aging group. The average age of patients was 70.40 (95% CI: 69.10-71.69) years, with 137 males (63.4%). Compared with the non-accelerated aging group, patients in the accelerated aging group were older, with a higher proportion of males, and a higher prevalence of hypertension, stable angina pectoris, and unstable angina pectoris. Multivariate Logistic regression analysis indicated that the absolute value of neutrophils (NEUT#), urea (UREA), adenosine deaminase (ADA), and the triglyceride-glucose index (TyG) were risk factors for accelerated aging, while cholinesterase (CHE) was a protective factor. For each unit increase in NEUT#, UREA, ADA, and TyG, the risk of aging increased by 64%, 48%, 10%, and 789%, respectively. The overall area under the receiver operating characteristic (ROC) curve of the model in the training set was 0.894, with a 95% confidence interval (CI) of 0.851-0.938.
UNASSIGNED: NEUT#, CHE, UREA, ADA, and TyG are predictors of accelerated aging in patients with T2DM and CHD, with the model showing favorable overall predictive performance.
摘要：
■探讨2型糖尿病(T2DM)合并冠心病(CHD)患者加速衰老的影响因素。
■选择2019年8月至2023年8月在徐州市中心医院诊断为T2DM和CHD的216例患者。患者分为衰老组和非衰老组，基于表型年龄加速度(PhenoAgeAccel)的正值或负值。进行Logistic回归分析。多变量分析中包含单变量分析P<0.05的变量，以确定影响T2DM和CHD患者衰老的因素。并报告模型曲线下面积。
■这项研究包括216名患者，加速老化组89人，非加速老化组127。患者平均年龄为70.40岁(95%CI:69.10-71.69),男性137人(63.4%)。与非加速老化组相比，加速老化组的患者年龄较大，男性比例较高，高血压的患病率更高，稳定型心绞痛,和不稳定型心绞痛.多因素Logistic回归分析显示中性粒细胞绝对值(NEUT#),尿素(UREA),腺苷脱氨酶(ADA),甘油三酯-葡萄糖指数（TyG）是加速衰老的危险因素，胆碱酯酶（CHE）是保护因素。对于NEUT#的每个单位增加，尿素,ADA,和TyG,衰老的风险增加了64%，48%,10%,和789％，分别。训练集中模型的受试者工作特征（ROC）曲线下的总面积为0.894，95％置信区间（CI）为0.851-0.938。
■NEUT#,CHE,尿素,ADA,和TyG是T2DM和CHD患者加速衰老的预测因子，该模型显示出良好的整体预测性能。
■选择2019年8月至2023年8月在徐州市中心医院诊断为T2DM和CHD的216例患者。患者分为衰老组和非衰老组，基于表型年龄加速度(PhenoAgeAccel)的正值或负值。进行Logistic回归分析。多变量分析中包含单变量分析P<0.05的变量，以确定影响T2DM和CHD患者衰老的因素。并报告模型曲线下面积。
■这项研究包括216名患者，加速老化组89人，非加速老化组127。患者平均年龄为70.40岁(95%CI:69.10-71.69),男性137人(63.4%)。与非加速老化组相比，加速老化组的患者年龄较大，男性比例较高，高血压的患病率更高，稳定型心绞痛,和不稳定型心绞痛.多因素Logistic回归分析显示中性粒细胞绝对值(NEUT#),尿素(UREA),腺苷脱氨酶(ADA),甘油三酯-葡萄糖指数（TyG）是加速衰老的危险因素，胆碱酯酶（CHE）是保护因素。对于NEUT#的每个单位增加，尿素,ADA,和TyG,衰老的风险增加了64%，48%,10%,和789％，分别。训练集中模型的受试者工作特征（ROC）曲线下的总面积为0.894，95％置信区间（CI）为0.851-0.938。
■NEUT#,CHE,尿素,ADA,和TyG是T2DM和CHD患者加速衰老的预测因子，该模型显示出良好的整体预测性能。
