The Risk and Influencing Factors of Vascular Dementia in Middle-aged and Elderly People in Kunming
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摘要:
目的 探讨血管性痴呆(vascular dementia,VD)发病影响因素,构建含血清学指标与临床指标的诺莫图模型。 方法 选取2019年1月至2023年12月于昆明医科大学第一附属医院体检科参加体检的中老年人群500例,统计VD发生风险,采用单、多因素分析VD发生影响因素,并绘制诺莫图模型,采用受试者工作特征曲线(ROC)及曲线下面积(AUC)、校准曲线、决策曲线(DCA)分析诺莫图模型诊断效能,并根据诺莫图风险得分建立风险分层系统。 结果 (1)中老年人群患者中VD发生率为10.00%;(2)高血压、脑卒中及血清KLK6、Klotho蛋白、NRG-1是中老年人群VD发生影响因素(P < 0.05);(3)诺莫图模型在中老年人群VD发生中诊断AUC为0.851(95%CI:0.794~0.908),诊断概率与实际概率一致,当阈值概率处于0.00~0.78时,诺莫图模型临床净收益率最大;(4)采用诺莫图模型诊断个体VD发生危险评分根据递归分割法进行风险等级划分,高风险患者VD发生率18.00%高于中等风险患者10.00%、低风险4.00%患者(P < 0.05)。 结论 昆明地区中老年人群VD发生率为10%,其影响因素涉及高血压、脑卒中及血清KLK6、Klotho蛋白、NRG-1。加强上述因素监测及干预对降低VD发生意义重大。 Abstract:Objective To explore the factors influencing the onset of vascular dementia (VD), a nomogram model was constructed, incorporating both serological and clinical indicators. Methods In the Physical Examination Department of the First Affiliated Hospital of Kunming Medical University, 500 middle-aged and elderly people who participated in physical examinations from January 2019 to December 2023 were selected to statistically analyze the risk of VD. The single and multiple factors that affect the occurrence of VD were analyzed, and a nomogram model was drawn. The receiver operating characteristic curve (ROC), area under the curve (AUC), calibration curve, and decision curve (DCA) were used to analyze the diagnostic performance of the nomogram model. A risk stratification system was established based on the risk score of the nomogram. Results (1) The incidence of VD in middle-aged and elderly patients was 10.00%; (2) Hypertension, stroke, and serum KLK6, Klotho protein, and NRG-1 were factors affecting the occurrence of VD in middle-aged and elderly patients (P < 0.05); (3) The diagnostic AUC of the nomogram model in the occurrence of VD in middle-aged and elderly patients was 0.851 (95%CI: 0.794-0.908), and the diagnostic probability was consistent with the actual probability. When the threshold probability was between 0.00 and 0.78, the clinical net benefit of the nomogram model was maximized; (4) Using the nomogram model to diagnose individual VD risk scores based on the recursive segmentation method for risk classification, the incidence of VD in high-risk patients was 18.00%, which was higher than that in moderate-risk patients (10.00%) and low-risk patients (4.00%) (P < 0.05). Conclusion The incidence of VD in middle-aged and elderly people in Kunming region is 10%, and its influencing factors involve hypertension, stroke, and serum KLK6, Klotho protein, NRG-1. Strengthening the monitoring and intervention of these factors is of great significance for reducing the incidence of VD. -
表 1 昆明地区中老年人群血管性痴呆发生单因素分析[($\bar x \pm s $)/n(%)]
Table 1. Univariate analysis of the incidence of vascular dementia in middle-aged and elderly people in Kunming region [($ \bar x \pm s $)/n(%)]
项目 VD组(n=50) 非VD组(n=450) t/χ2 P 性别 0.028 0.867 男 37(74.00) 328(72.89) 女 13(26.00) 122(27.11) 年龄(岁) 56.84±4.12 57.43±3.76 1.042 0.298 BMI(kg/m2) 22.84±1.22 22.76±1.34 0.404 0.686 MMSE评分(分) 23.02±0.40 27.27±1.33 22.465 <0.001* ADL评分(分) 64.92±6.11 66.08±5.79 1.337 0.182 HIS评分(分) 8.42±0.46 6.63±0.50 24.198 <0.001* 基础疾病 高血压 19(38.00) 72(16.00) 14.630 <0.001* 糖尿病 17(34.00) 63(14.00) 13.393 <0.001* 高脂血症 10(20.00) 76(16.89) 0.306 0.580 高尿酸血症 8(16.00) 63(14.00) 0.148 0.701 慢性牙周炎 15(30.00) 81(18.00) 4.177 0.041* 脑卒中 29(58.00) 162(36.00) 9.226 0.002* 受教育程度 0.328 0.742 初中 6(12.00) 45(10.00) 高中 11(22.00) 97(21.56) 大专及以上 33(66.00) 308(68.44) 吸烟史 15(30.00) 148(32.89) 0.171 0.680 饮酒史 20(40.00) 162(36.00) 0.311 0.577 每周运动次数(次) 16.006 <0.001* ≤3 29(58.00) 135(30.00) >3 21(42.00) 315(70.00) 每次运动时间(min) 13.711 <0.001* ≤30 36(72.00) 200(44.44) >30 14(28.00) 250(55.56) 血清学指标 RBC(×1012/L) 5.56±0.33 5.48±0.41 1.332 0.183 Hb(g/L) 142.42±13.38 140.99±14.67 0.660 0.510 WBC(×109/L) 6.75±1.12 6.80±1.00 0.331 0.741 PLT(×109/L) 165.65±18.81 167.13±16.99 0.578 0.564 KLK6(ng/mL) 3.70±1.11 2.61±0.75 9.224 <0.001* Aβ1-42(ng/L) 93.70±10.44 83.02±8.66 8.094 <0.001* Klotho蛋白(pg/mL) 166.62±49.88 216.64±64.79 5.286 <0.001* NRG-1(pg/mL) 270.49±81.01 352.22±105.26 5.316 <0.001* *P < 0.05。 表 2 赋值情况
Table 2. The assignment situation
自变量 赋值分层 X1 MMSE评分 原值代入 X2 HIS评分 原值代入 X3 高血压 有=1,否=0 X4 糖尿病 有=1,否=0 X5 慢性牙周炎 有=1,否=0 X6 每周运动次数 ≤3次=1,>3次=2 X7 每次运动时间 ≤30 min=1,>30 min=2 X8 KLK6 原值代入 X9 Aβ1-42 原值代入 X10 Klotho蛋白 原值代入 X11 NRG-1 原值代入 X12 脑卒中 有=1,否=0 表 3 昆明地区中老年人群VD发生多因素分析
Table 3. Multivariate analysis of VD incidence in middle-aged and elderly people in kunming region
自变量 β S.E. Waldχ2 OR 95%CI P 高血压(以否为参照) 0.992 0.324 9.383 2.698 1.334~5.456 <0.001* 脑卒中(以否为参照) 1.008 0.308 10.714 2.741 1.123~6.688 <0.001* KLK6 1.218 0.342 12.680 3.380 1.142~10.003 <0.001* Klotho蛋白 −0.621 0.151 16.917 0.537 0.405~0.713 <0.001* NRG-1 −0.708 0.186 14.490 0.493 0.378~0.642 <0.001* 常量 1.545 0.349 19.592 4.687 <0.001* 注:HIS评分、MMSE评分与高血压、慢性牙周炎、糖尿病、每周运动次数、每次运动时间、Aβ1-42之间多重共线性较强,VIF值=9,将HIS评分、MMSE评分、慢性牙周炎、糖尿病、每周运动次数、每次运动时间、Aβ1-42剔除后多重共线性变弱,VIF值=2,最终仅纳入高血压、脑卒中、KLK6、Klotho蛋白、NRG-1;*P < 0.05。 -
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