作者：冶成芳，任映丽，王梦卉，孙乐，刘园园，李南方

单位：

830001新疆维吾尔自治区乌鲁木齐市，新疆维吾尔自治区人民医院高血压中心 新疆高血压研究所 国家卫生健康委高血 压诊疗研究重点实验室 新疆维吾尔自治区重点实验室“新疆高血压病研究实验室” 新疆高血压（心脑血管）疾病临床医学研究中心

Units：

Hypertension Center of People's Hospital of Xinjiang Uygur Autonomous Region/Xinjiang Hypertension Institute/National Health Committee Key Laboratory of Hypertension Clinical Research/Key Laboratory of Xinjiang Uygur Autonomous Region "Hypertension Research Laboratory" /Xinjiang Clinical Medical Research Center for Hypertension (Cardio-Cerebrovascular) Diseases, Urumqi 830001, China

关键词：

高血压前期；心血管疾病；预测；列线图

Keywords：

Prehypertension; Cardiovascular diseases; Forecasting; Nomograms

CLC：

R 543 R 54

DOI：

10.12114/j.issn.1008-5971.2023.00.307

Funds：

新疆维吾尔自治区重大科技专项项目（2022A03012-2）；新疆维吾尔自治区人民医院院内项目（20210133）

摘要：

目的　构建高血压前期人群发生心血管疾病的风险预测列线图模型。方法　从新疆维吾尔自治区人民 医院高血压中心2019年1月建立的塔城地区额敏县自然人群队列中选取高血压前期人群3 690例为研究对象。收集研究 对象一般资料、体格检查结果、实验室检查结果。从研究对象入组开始对其进行面对面随访或电话随访，每6个月随 访1次，随访时间截至2022年12月。根据随访结果，将研究对象分为对照组和心血管疾病组。采用多因素Logistic回归 分析探讨高血压前期人群发生心血管疾病的影响因素；基于多因素Logistic回归分析结果，采用R 3.6.3中的rms程序包 构建高血压前期人群发生心血管疾病的风险预测列线图模型；采用Hosmer-Lemeshow拟合优度检验评估该列线图模型 的拟合情况，采用ROC曲线评估该列线图模型的区分度，采用校准曲线评估该列线图模型的校准度。结果　随访结束 后共231例研究对象发生了心血管疾病，心血管疾病发生率为6.3%（231/3 690）。多因素Logistic回归分析结果显示， 年龄、心血管疾病家族史、吸烟、饮酒、锻炼情况、BMI、TC、血红蛋白是高血压前期人群发生心血管疾病的独立 影响因素（P＜0.05）。基于多因素Logistic回归分析结果，构建高血压前期人群发生心血管疾病的风险预测列线图模 型。Hosmer-Lemeshow拟合优度检验结果显示，该列线图模型的拟合情况较好（χ 2 =6.625，P=0.578）。ROC曲线分析 结果显示，该列线图模型预测高血压前期人群发生心血管疾病的曲线下面积为0.829〔95%CI（0.803，0.854）〕。校 准曲线分析结果显示，该列线图模型预测高血压前期人群的心血管疾病发生率与实际发生率基本一致。结论　年龄、 心血管疾病家族史、吸烟、饮酒、锻炼情况、BMI、TC、血红蛋白是高血压前期人群发生心血管疾病的独立影响因 素，而基于上述影响因素构建的高血压前期人群发生心血管疾病的风险预测列线图模型拟合情况较好，且具有较好的 区分度、校准度。

Abstract：

Objective To construct the nomogram model for predicting the risk of cardiovascular disease in prehypertensive populations. Methods A total of 3 690 persons with prehypertension were selected from the natural population cohort of Emin County, Tacheng District, established by Hypertension Center of People's Hospital of Xinjiang Uygur Autonomous Region in January 2019. General information, physical examination results and laboratory examination results were collected. The subjects were followed up face-to-face or by telephone evert 6 months from enrollment, and the follow-up period was up to December 2022. According to the follow-up results, the subjects were divided into control group and cardiovascular disease group. Multivariate Logistic regression analysis was used to explore the influencing factors of cardiovascular disease in prehypertensive population. Based on the results of multivariate Logistic regression analysis, the rms package in R 3.6.3 was used to construct the nomogram model for predicting the risk of cardiovascular disease in prehypertensive population. Hosmer-Lemeshow goodness of fit test was used to evaluate the fit of the nomogram model, ROC curve was used to evaluate the differentiation of the nomogram model, calibration curve was used to evaluate the calibration degree of the nomogram model. Results At the end of follow up, 231 subjects developed cardiovascular disease, the incidence of cardiovascular disease was 6.3% (231/3 690) . Multivariate Logistic regression analysis showed that age, family history of cardiovascular disease, smoking, drinking, exercise, BMI, TC and hemoglobin were independent influencing factors of cardiovascular disease in prehypertensive population (P < 0.05) . Based on the results of multivariate Logistic regression analysis, the nomogram model for predicting the risk of cardiovascular disease in prehypertensive population was constructed. The Hosmer-Lemeshow goodness of fit test showed that the nomogram model was well fitted ( χ 2 =6.625, P=0.578) . The ROC curve analysis results showed that the area under the curve of the nomogram model in predicting cardiovascular disease in the prehypertensive population was 0.829 [95%CI (0.803, 0.854) ] . The results of calibration curve analysis showed that the incidence of cardiovascular disease in prehypertensive population predicted by the nomogram model was basically consistent with the actual incidence. Conclusion Age, family history of cardiovascular disease, smoking, drinking, exercise, BMI, TC, and hemoglobin are independent influencing factors of cardiovascular disease in prehypertensive population. In this study, the nomogram model for predicting the risk of cardiovascular disease in prehypertensive population constructed based on the above influencing factors is well fitted, and has a good degree of differentiation and calibration.

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