Establishment and verification of clinical prediction model of hypertension complicated with diabetes in elderly people in community
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摘要:
目的 分析社区老年高血压患者发生糖尿病的危险因素,并构建预测模型,以期为社区老年高血压患者合并糖尿病的防控提供参考依据。 方法 收集2023年4月—2024年3月在团结新村社区卫生服务中心参与慢性病管理的1 859例≥65岁老年高血压患者的临床资料。将数据采用简单随机抽样的方法按7∶3的比例拆分为训练集(1 301例)和验证集(558例),通过LASSO回归对变量降维,进行多因素logistic回归分析研究高血压合并糖尿病的危险因素,构建Nomogram预测模型,并使用验证集进行内部验证。使用受试者工作特征曲线评估模型区分度,绘制校正曲线并进行H-L检验评估模型一致性,通过决策分析评估模型有效性。 结果 在1 859例社区老年高血压患者中,有546人(29.37%)患有糖尿病。多因素logistic回归显示,慢性病家族史、乏力、胸闷和嗜糖均为高血压合并糖尿病的独立危险因素;而认知功能较好和日常锻炼则为保护性因素。训练集构建预测模型的AUC为0.873(95% CI:0.850~0.873),校正曲线斜率接近1,且H-L拟合优度检验χ2=6.511,P=0.260,一致性较好。决策曲线提示模型能够产生净获益。 结论 该社区老年人高血压合并糖尿病的患病率较高,基于社区可测量的6个临床特征构建的预测模型在预测高血压合并糖尿病的发生时表现出良好的预测能力和临床应用价值。 Abstract:Objective The objective of this study is two-fold: firstly, to analyze the risk factors associated with diabetes in elderly patients suffering from hypertension in the community, and secondly, to construct a prediction model. The ultimate aim of this study is to provide a reference for the prevention and management of diabetes in elderly patients suffering from hypertension in the community. Methods From April 2023 to March 2024, the clinical data of 1 859 elderly patients with hypertension aged 65 years and over who participated in chronic disease management in the Tuanjie Community Health Service Centre were collected for the purpose of the study. The data were randomly partitioned into a training set comprising 1 301 cases and a validation set consisting of 558 cases, at a ratio of 7∶3 by means of a simple random sampling method. The LASSO regression method was employed to reduce the dimensionality of the variables, while multivariate logistic regression analysis was conducted to investigate the risk factors associated with hypertension in conjunction with diabetes. Subsequently, a Nomogram prediction model was developed. The validation set was utilized for the purpose of internal validation. The receiver operating characteristic curve (AUC) was employed to evaluate the discrimination of the model, the calibration curve was delineated and the Hosmer-Lemeshow test was used to evaluate the consistency of the model, and the decision analysis was used to evaluate the validity of the model. Results In a study of 1 859 elderly hypertensive patients, 546 (29.37%) were found to have diabetes mellitus. Multivariate logistic regression analysis demonstrated that a family history of chronic diseases, fatigue, chest tightness and sugar addiction were independent risk factors for hypertension combined with diabetes. Nevertheless, superior cognitive function and the undertaking of daily exercise were found to be protective factors. The area under the curve (AUC) of the prediction model constructed from the training set was 0.873 (95% CI: 0.850-0.873). The calibration curve' s slope was close to 1, and the H-L goodness of fit test yielded a chi-squared value of 6.511, a P value of 0.260, and good consistency. The decision curve indicated a net benefit from the model. Conclusion The prevalence of hypertension in combination with diabetes is high among the elderly population in this community. The prediction model, which is based on six community-measurable clinical characteristics, demonstrates both good predictive ability and clinical application value in predicting the occurrence of hypertension in combination with diabetes. -
Key words:
- Hypertension /
- Diabetes /
- Community /
- Elderly /
- Predictive model
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表 1 高血压患者合并糖尿病影响因素的单因素分析[例(%)]
Table 1. Univariate analysis of influencing factors of hypertension combined with diabetes [cases (%)]
变量 高血压合并糖尿病组(n=382) 单纯高血压组
(n=919)合计
(n=1 301)统计量 P值 性别 2.364a 0.124 男性 171(44.8) 369(40.2) 540(41.5) 女性 211(55.2) 550(59.8) 761(58.5) 年龄 -0.031b 0.975 65~74岁 213(55.8) 516(56.1) 729(56.0) 75~84岁 125(32.7) 292(31.8) 417(32.1) ≥85岁 44(28.4) 111(12.1) 155(11.9) 民族 6.437a 0.011 汉族 371(97.1) 910(99.0) 1 281(98.5) 少数民族 11(2.9) 9(1.0) 20(1.5) 文化程度 -0.494b 0.621 小学及以下 80(20.9) 176(19.2) 256(19.7) 初中或高中 235(61.5) 616(67.0) 851(65.4) 专科及以上 67(17.5) 127(13.8) 194(14.9) 医疗保险 367(96.1) 874(95.1) 1 241(95.4) 0.577a 0.447 药物过敏史 34(8.9) 54(5.9) 88(6.8) 3.914a 0.048 慢性病家族史 102(26.7) 161(17.5) 263(20.2) 25.066a <0.001 头晕 39(10.2) 51(5.5) 90(6.9) 9.100a 0.003 乏力 44(11.5) 14(1.5) 58(4.5) 63.287a <0.001 胸闷 28(7.3) 21(2.3) 49(3.8) 18.947a <0.001 腹型肥胖 168(44.0) 407(44.3) 575(44.2) 0.010a 0.919 肥胖 42(11.0) 108(11.8) 150(11.5) 0.152a 0.697 健康满意度 18.374a <0.001 满意 308(80.6) 822(89.4) 1 130(86.9) 不满意 74(19.4) 97(10.6) 171(13.1) 自理能力 1.521a 0.217 可自理 353(92.4) 866(94.2) 1 219(93.7) 不自理 29(7.6) 53(5.8) 82(6.3) 认知功能 439.513a <0.001 阴性 113(29.6) 806(87.7) 919(70.6) 阳性 269(70.4) 113(12.3) 382(29.4) 情感状态 42.528a <0.001 阴性 317(83.0) 867(94.3) 1 184(91.0) 阳性 65(17.0) 52(5.7) 117(9.0) 锻炼 304(79.6) 805(87.6) 1 109(85.2) 13.776a <0.001 嗜糖 96(25.1) 13(1.4) 109(8.4) 197.719a <0.001 饮酒 79(20.7) 110(12.0) 189(14.5) 16.491a <0.001 吸烟 100(26.2) 150(16.3) 250(19.2) 16.885a <0.001 注:a为χ2值,b为Z值。 表 2 变量赋值情况
Table 2. Variable assignment
变量 赋值方法 变量 赋值方法 高血压合并糖尿病 是=1,否=0 民族 汉族=1,少数民族=0 药物过敏史 有=1,无=0 头晕 有=1,无=0 慢性病家族史 有=1,无=0 乏力 有=1,无=0 健康满意度 满意=1,不满意=0 胸闷 有=1,无=0 认知功能 阳性=1,阴性=0 锻炼 是=1,否=0 情感状态 阳性=1,阴性=0 嗜糖 是=1,否=0 饮酒 是=1,否=0 吸烟 是=1,否=0 表 3 高血压合并糖尿病影响因素的logistic回归分析
Table 3. Logistic regression analysis of influencing factors of hypertension combined with diabetes
变量 B SE Waldχ2 P值 OR值(95% CI) 慢性病家族史 0.690 0.199 12.048 < 0.001 1.994(1.350~2.350) 乏力 2.157 0.397 29.587 < 0.001 8.647(3.974~18.811) 胸闷 1.085 0.405 7.184 0.007 2.960(1.339~6.545) 认知功能 -2.856 0.171 278.646 < 0.001 0.057(0.041~0.080) 锻炼 -0.725 0.220 10.839 < 0.001 0.485(0.315~0.745) 嗜糖 3.120 0.348 80.278 < 0.001 22.649(11.445~44.818) -
[1] 刘明波, 何新叶, 杨晓红, 等. 《中国心血管健康与疾病报告2023》要点解读[J]. 中国心血管杂志, 2024, 29(4): 305-324.LIU M B, HE X Y, YANG X H, et al. Interpretation of Report on Cardiovascular Health and Diseases in China 2023[J]. Chinese Journal of Cardiovascular Medicine, 2024, 29(4): 305-324. [2] 中国高血压防治指南修订委员会, 高血压联盟(中国), 中国医疗保健国际交流促进会高血压病学分会, 等. 中国高血压防治指南(2024年修订版)[J]. 中华高血压杂志(中英文), 2024, 32(7): 603-700.Chinese Committee for the Revision of Guidelines for the Prevention and Treatment of Hypertension, Hypertension Alliance (China), Hypertension Branch of Chinese International Exchange and Promotion Association for Medical and Health Care, etc. Chinese guidelines for the prevention and treatment of hypertension (2024 revision)[J]. Chinese Journal of Hypertension, 2024, 32(7): 603-700. [3] 《中国老年型糖尿病防治临床指南》编写组. 中国老年2型糖尿病防治临床指南(2022年版)[J]. 中国糖尿病杂志, 2022, 30(1): 2-51.Writing group of Clinical guidelines for the prevention and treatment of elderly diabetes in China. Clinical guidelines for the prevention and treatment of type 2 diabetes in the elderly in China (2022 edition)[J]. Chinese Journal of Diabetes, 2022, 30(1): 2-51. [4] 刘冬阳, 黄昕彤, 赖晋锋, 等. 中国中老年人慢性病共病流行趋势研究[J]. 中国慢性病预防与控制, 2024, 32(4): 244-249.LIU D Y, HUANG X T, LAI J F, et al. Prevalence of multiple chronic conditions in middle-aged and elderly people in China[J]. Chinese Journal of Prevention and Control of Chronic Diseases, 2024, 32(4): 244-249. [5] 王庭俊, 张玲玉, 徐国焱, 等. 加强全科规范化培训医师医患沟通技能培养, 提高社区慢性疾病管理水平[J]. 中华高血压杂志(中英文), 2024, 32(6): 501-504.WANG T J, ZHANG L Y, XU G Y, et al. To strengthen the doctor-patient communication skills of general practice standardized training physicians and improve the level of chronic disease management in community[J]. Chinese Journal of Hypertension, 2024, 32(6): 501-504. [6] 杨洪燕, 夏淼, 刘赞朝, 等. 2型糖尿病视网膜病变临床预测模型的构建与评价[J]. 中国慢性病预防与控制, 2023, 31(1): 2-7.YANG H Y, XIA M, LIU Z Z, et al. Establishment and evaluation of a clinic prediction model of diabetic retinopathy in patients with type 2 diabetes mellitus[J]. Chinese Journal of Prevention and Control of Chronic Diseases, 2023, 31(1): 2-7. [7] 冯晓晨, 王永强, 王欣, 等. 日常生活活动能力对慢性病共病老年人认知功能的影响: 社会参与和抑郁的链式中介效应[J]. 现代预防医学, 2024, 51(19): 3576-3582.FENG X C, WANG Y Q, WANG X, et al. The impact of activities of daily living on cognitive function in elderly in-dividuals with chronic comorbidities: the chain mediating effects of social participation and depression[J]. Modern Preventive Medicine, 2024, 51(19): 3576-3582. [8] 傅晨, 王开军. 决定系数与相关系数辅助的LASSO回归[J]. 福建师范大学学报(自然科学版), 2024, 40(2): 57-63.FU C, WANG K J. LASSO Regression Assisted by Coefficient of Determination and Correlation Coefficient[J]. Journal of Fujian Normal University (Natural Science Edition), 2024, 40(2): 57-63. [9] BINUYA M A E, ENGELHARDT E G, SCHATS W, et al. Methodological guidance for the evaluation and updating of clinical prediction models: a systematic review[J]. BMC Med Res Methodol, 2022, 22(1): 316. DOI: 10.1186/s12874-022-01801-8. [10] COLLINS G S, MOONS K G M, DHIMAN P, et al. TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods[J]. BMJ, 2024, 385: e078378. DOI: 10.1136/bmj-2023-078378. [11] 奚丽婧, 郭昭艳, 杨雪珂, 等. LASSO及其拓展方法在回归分析变量筛选中的应用[J]. 中华预防医学杂志, 2023, 57(1): 107-111.XI L J, GUO Z Y, YANG X K, et al. Application of LASSO and its extended method in variable selection of regression analysis[J]. Chinese Journal of Preventive Medicine, 2023, 57(1): 107-111. [12] 刘奇. 高血压合并糖尿病前期中医证候特点及相关心血管危险因素研究[D]. 乌鲁木齐: 新疆医科大学, 2021.LIU Q. Traditional Chinese medicine syndrome characteristics and related cardiovascular risk factors of hypertension combined with prediabetes[D]. Urumqi: Xinjiang Medical University, 2021. [13] 王亦南, 杨晗, 樊秀艳. 健康生活方式对老年慢性病患者的干预效果研究[J]. 中国公共卫生管理, 2024, 40(1): 92-94.WANG Y N, YANG H, FAN X Y. Study on intervention effect of healthy lifestyle on elderly patients with chronic diseases[J]. Chinese Journal of Public Health Management, 2024, 40(1): 92-94. [14] 刘洪颖. 2型糖尿病合并高血压患者轻度认知功能障碍现况研究[D]. 长沙: 中南大学, 2023.LIU H Y. Current status of mild cognitive impairment in patients with type 2 diabetes mellitus and hypertension[D]. Changsha: Central South University, 2023. [15] JIA G, SOWERS J R. Hypertension in diabetes: an update of basic mechanisms and clinical disease[J]. Hypertension, 2021, 78(5): 1197-1205. [16] 陈超, 胡龙刚, 安毅. 肠道菌群及其代谢产物与心血管疾病关系的研究进展[J]. 青岛大学学报(医学版), 2023, 59(6): 937-940.CHEN C, HU L G, AN Y. Research advances in the relationship of gut microbiota and their metabolites with cardiovascu-lar diseases[J]. Journal of Qingdao University(Medical Sciences), 2023, 59(6): 937-940. [17] 张颖, 付妤. 能量代谢与炎症免疫研究进展[J]. 医学研究杂志, 2022, 51(4): 6-9.ZHANG Y, FU Y. Research progress of energy metabolism and inflammatory immunity[J]. Journal of Medical Research, 2022, 51(4): 6-9. [18] 田雪, 黄柳, 姚菁青, 等. 血清脂蛋白相关磷脂酶A2水平与颈动脉粥样硬化斑块的相关性分析[J]. 中华全科医学, 2022, 20(11): 1848-1851. doi: 10.16766/j.cnki.issn.1674-4152.002717TIAN X, HUANG L, YAO J Q, et al. Correlation analysis between serum Lp-PLA2 level and carotid atherosclerotic plaque[J]. Chinese Journal of General Practice, 2022, 20(11): 1848-1851. doi: 10.16766/j.cnki.issn.1674-4152.002717 [19] 蒋小荣, 王燕君, 王小惠. 综合护理对改善老年高血压合并2型糖尿病患者血压、血糖水平的效果观察[J]. 心血管病防治知识, 2021, 11(14): 44-45.JIANG X R, WANG Y J, WANG X H. Effect of comprehensive nursing on improving blood pressure and blood glucose levels in elderly patients with hypertension and type 2 diabetes[J]. Prevention and Treatment of Cardiovascular Disease, 2021, 11(14): 44-45. [20] 谷鸿秋. 临床预测模型的困境与机遇[J]. 中国卒中杂志, 2024, 19(5): 481-487.GU H Q. Challenges and Opportunities in Clinical Prediction Models[J]. Chinese Journal of Stroke, 2024, 19(5): 481-487. -