摘要
目的探究血清血尿酸(SUA)及甲状腺激素水平与2型糖尿病(T2DM)患者发生动脉粥样硬化性心血管疾病(ASCVD)的关系,并构建发生风险预测模型。方法回顾性选取2020年5月至2023年5月丽水市人民医院内分泌科诊治的326例T2DM患者,根据是否发生ASCVD,将其分为发生组(n=152)与未发生组(n=174)。收集所有研究对象临床资料以血清SUA及甲状腺激素(TT3、TT4、FT3、FT4、TSH)水平。采用单因素logistic回归、多因素logistic回归分析T2DM患者发生ASCVD的危险因素,依据危险因素构建T2DM患者发生ASCVD的风险列线图预测模型。结果两组对象年龄、空腹血糖、糖尿病病程、三酰甘油、SUA、TSH水平比较,差异有统计学意义(P<0.05),除此外,两组其他资料比较差异无统计学意义(P>0.05)。二元logistics回归结果显示,年龄大、糖尿病病程长、三酰甘油高、SUA水平高、TSH水平高为T2DM患者发生ASCVD的独立危险因素(P<0.05)。受试者工作特征(ROC)曲线分析结果显示,年龄、糖尿病病程、三酰甘油、SUA、TSH及列线图预测模型的ROC曲线下面积(AUC)分别为0.711、0.702、0.668、0.755、0.965、0.987,可知,均对T2DM患者发生ASCVD有较好的预测价值。当取cut-off时,各自敏感度分别为0.638、0.539、0.638、0.730、0.941、0.960,特异度分别为0.690、0.799、0.644、0.661、0.943、0.954。Bootstrap法(B=1000)对列线图预测模型进行内部验证显示,Bias-corrected预测曲线与Ideal线基本重合,C-index为0.975,该模型预测能力较好。决策曲线显示,该模型的阈值概率范围为0.01~0.98,其净收益率>0。结论血清SUA及甲状腺激素水平是预测T2DM患者发生ASCVD的重要指标,构建的风险列线图预测模型具有较好的预测性能和临床应用价值。
Objective To investigate the relationship between serum uric acid(SUA)levels,thyroid hormones,and the occurrence of atherosclerotic cardiovascular disease(ASCVD)in patients with type 2 diabetes mellitus(T2DM),and to construct a risk prediction model for occurrence.Methods A retrospective study was conducted on 326 T2DM patients treated in the Department of Endocrinology at Lishui People′s Hospital from May 2020 to May 2023.Patients were divided into the occurrence group(n=152)and non-occurrence group(n=174)based on whether ASCVD occurred.Clinical data and serum levels of SUA and thyroid hormones(TT3,TT4,FT3,FT4,TSH)were collected for all subjects.Univariate and multivariate logistic regression analyses were used to analyze the risk factors for ASCVD in T2DM patients,and a risk nomogram prediction model for ASCVD in T2DM patients was constructed based on these factors.Results There were statistically significant differences in age,fasting blood glucose,duration of diabetes,triglycerides,SUA,and TSH levels between the two groups(P<0.05).However,there were no differences in other variables between the two groups(P>0.05).Binary logistic regression analysis showed that older age,longer duration of diabetes,higher triglyceride levels,higher SUA levels,and higher TSH levels were independent risk factors for ASCVD in T2DM patients(P<0.05).The ROC curve analysis results showed that the area under the ROC curve AUC of age,duration of diabetes,triglycerides,SUA,TSH,and the nomogram prediction model were 0.711,0.702,0.668,0.755,0.965,and 0.987,respectively,indicating good predictive value for ASCVD in T2DM patients.When the cut-off values were determined,the sensitivities were 0.638,0.539,0.638,0.730,0.941,and 0.960,respectively,and the specificities were 0.690,0.799,0.644,0.661,0.943,and 0.954,respectively.Bootstrap validation of the nomogram prediction model(B=1000)showed that the bias-corrected prediction curve overlapped well with the ideal curve,with a C-index of 0.975,indicating good predictive ability of the model.D
作者
叶斌
季晓珍
朱向盈
季美霞
YE Bin;JI Xiao-zhen;ZHU Xiang-ying;JI Mei-xia(Department of Endocrinology,Lishui People′s Hospital,Lishui 323000,Zhejiang,China)
出处
《广东医学》
CAS
2024年第6期744-750,共7页
Guangdong Medical Journal
基金
2022年浙江省卫生健康科技计划(2022ZH022)。
关键词
2型糖尿病
血尿酸
甲状腺激素水平
动脉粥样硬化性心血管疾病
影响因素
预测模型
type 2 diabetes
blood uric acid
thyroid hormone levels
atherosclerotic cardiovascular disease
influencing factors
prediction model
