Objective: This study aimed to analyze clinical factors related to arterial stiffening and establish a risk prediction nomogram of arterial stiffening in the octogenarian(≥80 years). Methods: This study was a retrospective cross-sectional study, which enrolled the octogenarian elderly who underwent physical examination and secondary prevention intervention in the outpatient department of Chinese People's Liberation Army General Hospital from April 2022 to August 2022. Clinical data including demographics, biochemical indicators and medical history were collected. Brachial-ankle pulse wave velocity (baPWV) was detected during the clinical visit. Participants were divided into the control group (baPWV≤1 800 cm/s) and vascular sclerosis group (baPWV>1 800 cm/s). The risk factors of arterial stiffness were analyzed by univariate and logistic regression analysis, and the nomogram model was constructed by R programming language. The predictive effect of the nomogram model was evaluated by the receiver operating characteristic curve (ROC). Results: The median age of the 525 participants was 87.0 (82.0, 92.0) years, 504 (96.0%) were male, 82 in the control group, 443 in the vascular sclerosis group. The baPWV, age, systolic blood pressure, mean arterial pressure and diastolic blood pressure were significantly lower in the control group than those in the vascular sclerosis group (all P<0.05). Logistic regression analysis showed that high-density lipoprotein cholesterol, alanine aminotransferase and amylase were protective factors, and alkaline phosphatase and creatinine were risk factors of arterial stiffening (all P<0.05). The combined nomogram model scores including age, mean arterial pressure and the above five laboratory indicators indicated that mean arterial pressure and serum creatinine levels were strongly correlated with vascular sclerosis. The ROC curve suggested that the nomogram model had good prediction ability. Conclusions: Age, mean arterial pressure, high-density lipoprotein cholesterol, alanine aminotransferase, alkaline phosphatase, amylase and creatinine are independently determinants for increased vascular stiffness. The combined prediction model in this study can provide reference for individualized clinical risk prediction of vascular sclerosis in the octogenarian elderly.
目的： 分析高龄人群（≥80岁）动脉僵硬度升高的相关影响因素，建立高龄人群血管硬化风险列线图模型，为高龄人群血管疾病防控提供依据。 方法： 本研究为回顾性横断面研究。纳入2022年4—8月于解放军总医院门诊体检的高龄人群，收集人口学、生化指标及药物治疗等临床资料，同期检测肱踝动脉脉搏波传导速度（baPWV）并分为2组，baPWV≤1 800 cm/s为对照组，baPWV>1 800 cm/s为血管硬化组。通过单因素分析和多因素logistic回归分析动脉僵硬度升高的相关影响因素，采用R软件构建其列线图模型，通过受试者工作特征曲线（ROC）评价列线图模型的预测效果。 结果： 525名高龄人群中，年龄87.0（82.0，92.0）岁，其中男性504名（96.0%）。对照组82名，血管硬化组443例。对照组的baPWV、年龄、收缩压、平均动脉压和舒张压水平低于血管硬化组（P均<0.05）。多因素logistic回归分析显示，高密度脂蛋白胆固醇、谷丙转氨酶和淀粉酶是动脉僵硬度升高的保护因素；碱性磷酸酶和肌酐是其危险因素（P均<0.05）。年龄、平均动脉压和上述5项实验室指标联合的列线图模型评分提示平均动脉压和血肌酐水平与血管硬化呈强相关。ROC曲线提示列线图模型预测效果较好。 结论： 年龄、平均动脉压、高密度脂蛋白胆固醇、谷丙转氨酶、碱性磷酸酶、淀粉酶和肌酐是动脉僵硬度升高的独立影响因素。本研究构建的联合预测模型可为临床个体化预测高龄人群血管硬化风险提供参考。.