• 中国精品科技期刊
  • 《中文核心期刊要目总览》收录期刊
  • RCCSE 中国核心期刊(5/114,A+)
  • Scopus收录期刊
  • 美国《化学文摘》(CA)收录期刊
  • WHO 西太平洋地区医学索引(WPRIM)收录期刊
  • 《中国科学引文数据库(CSCD)》核心库期刊 (C)
  • 中国科技核心期刊
  • 中国科技论文统计源期刊
  • 《日本科学技术振兴机构数据库(中国)》(JSTChina)收录期刊
  • 美国《乌利希期刊指南》(UIrichsweb)收录期刊
  • 中华预防医学会系列杂志优秀期刊(2019年)

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于机器学习和logistic回归分析模型分析2型糖尿病轻度认知功能障碍的影响因素

张红梅 张宁 孙玉娇 张洲

张红梅, 张宁, 孙玉娇, 张洲. 基于机器学习和logistic回归分析模型分析2型糖尿病轻度认知功能障碍的影响因素[J]. 中华疾病控制杂志, 2024, 28(3): 269-276. doi: 10.16462/j.cnki.zhjbkz.2024.03.004
引用本文: 张红梅, 张宁, 孙玉娇, 张洲. 基于机器学习和logistic回归分析模型分析2型糖尿病轻度认知功能障碍的影响因素[J]. 中华疾病控制杂志, 2024, 28(3): 269-276. doi: 10.16462/j.cnki.zhjbkz.2024.03.004
ZHANG Hongmei, ZHANG Ning, SUN Yujiao, ZHANG Zhou. Influential factors of mild cognitive impairment in type 2 diabetes mellitus based on machine learning and logistic regression[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(3): 269-276. doi: 10.16462/j.cnki.zhjbkz.2024.03.004
Citation: ZHANG Hongmei, ZHANG Ning, SUN Yujiao, ZHANG Zhou. Influential factors of mild cognitive impairment in type 2 diabetes mellitus based on machine learning and logistic regression[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(3): 269-276. doi: 10.16462/j.cnki.zhjbkz.2024.03.004

基于机器学习和logistic回归分析模型分析2型糖尿病轻度认知功能障碍的影响因素

doi: 10.16462/j.cnki.zhjbkz.2024.03.004
基金项目: 

国家自然科学基金 82000775

南京大学中国医院改革发展研究院课题 NDYG2022078

详细信息
    通讯作者:

    张宁,E-mail:zjz1906@qq.com

  • 中图分类号: R587.1

Influential factors of mild cognitive impairment in type 2 diabetes mellitus based on machine learning and logistic regression

Funds: 

National Natural Science Foundation Project 82000775

Project of Nanjing University China Hospital Reform and Development Research Institute NDYG2022078

More Information
  • 摘要:   目的  应用机器学习和logistic回归分析模型分析2型糖尿病(type 2 diabetes mellitus, T2DM)轻度认知功能障碍的影响因素,为相关干预措施提供依据。  方法  收集南京鼓楼医院内分泌科1 284例T2DM患者的资料,将数据分为训练集(70%)和测试集(30%),分别采用logistic回归分析、随机森林、XGBoost模型对数据建模并进行可解释性分析。  结果  随机森林模型的预测性能最高,训练集的AUC值为1.0,测试集的AUC值为0.783(95% CI:0.660~0.894),模型筛选出T2DM患者发生轻度认知功能障碍的19个重要变量,如受教育时间、年龄、胰岛素敏感指数、周围神经病变、糖化血红蛋白、骨代谢异常等。  结论  随机森林模型的预测性能最佳,可以协助医务人员准确识别T2DM患者发生轻度认知功能障碍的危险因素,有助于医务人员对患者进行早期预防。
  • 图  1  T2DM患者发生MCI的多因素logistic回归分析模型

    T2DM: 2型糖尿病; MCI: 轻度认知功能障碍; GLP-1:胰高糖素样肽-1。

    Figure  1.  Multivariate logistic regression analysis model of MCI in T2DM patients

    T2DM: type 2 diabetes mellitus; MCI: mild cognitive impairment; GLP-1:glucagon-like peptide-1.

    图  2  随机森林模型的变量重要性排序

    Figure  2.  The importance ranking of variables in random forests model

    图  3  逐步随机森林模型袋外数据分类错误率

    Figure  3.  Classification error rate chart of stepwise random forest model out-of-bag data

    图  4  特征重要性排序图

    Figure  4.  Sorting chart of feature importance

    图  5  变量的SHAP摘要图

    Figure  5.  SHAP summary chart of variables

    图  6  Logistic回归分析模型、随机森林模型、XGBoost模型的ROC曲线

    AUC:曲线下面积。

    Figure  6.  ROC curve of logistic regression, random forest model, and XGBoost model

    AUC: area under curve.

    表  1  两组患者疾病资料的比较

    Table  1.   Comparison of disease data between two groups of patients

    变量variable 正常对照组
    Control group
    (n=865)
    MCI组
    group
    (n= 419)
    t/Z/χ2
    值value
    P
    value
    病程/年Course of disease /years 9.56±8.01 10.81±8.28 -2.56 0.010
    年龄/年Age/years 55.34±11.70 61.91±8.60 -11.36 < 0.001
    性别Gender 16.60 < 0.001
      男Male 605(69.94) 245(58.47)
      女Female 260(30.06) 174(41.53)
    受教育时间/年Years of education/years 12.97±3.24 10.41±3.35 13.15 < 0.001
    糖尿病家族史Family history of diabetes 467(53.99) 191(45.58) 7.65 0.006
    合并高血压Concomitant history of hypertension 407(47.05) 244(58.23) 14.12 < 0.001
    合并高血脂Concomitant history of hyperlipidemia 357(41.27) 147(35.08) 4.28 0.039
    体质指数/(kg·m-2) Body mass index/(kg·m-2) 24.84(23.03, 27.12) 24.14(22.23, 26.46) -3.54 < 0.001
    周围神经病变Diabetes peripheral neuropathy 235(27.17) 180(42.96) 31.46 < 0.001
    颈动脉斑块Complications of carotid artery plaques 471(54.45) 296(70.64) 30.11 < 0.001
    糖尿病肾病Complications of diabetic nephropathy 83(9.59) 58(13.84) 4.78 0.029
    骨代谢异常Abnormal bone metabolism 303(35.03) 217(51.79) -20.94 < 0.001
    下肢大血管病变Lower extremity atherosclerosis 408(47.17) 260(62.05) 24.46 < 0.001
    脑血管病史History of cerebrovascular diseases 83(9.60) 74(17.66) 16.37 < 0.001
    心血管病史History of cardiovascular 107(12.37) 85(20.29) 13.30 < 0.001
    使用GLP-1药物 Using GLP-1 medication 23(2.66) 13(3.10) 0.65 0.786
    三酰甘油/(mmol·L-1) Triglyceride/(mmol·L-1) 1.35(0.95, 2.06) 1.30(0.90, 1.83) -1.78 0.075
    胆固醇/(mmol·L-1) Cholesterol/(mmol·L-1) 4.53(3.79, 5.34) 4.45(3.70, 5.27) -1.21 0.225
    低密度脂蛋白胆固醇/(mmol·L-1) Low density lipoprotein cholesterol/(mmol·L-1) 2.64(2.00, 3.30) 2.99(2.32, 3.66) -5.52 < 0.001
    肾小球滤过率/(mL·min·1.73 m-2) Glomeruar filtration rate/(mL·min·1.73 m-2) 117.65(106.20, 135.60) 117.65(98.00, 134.05) -1.68 0.094
    尿酸/(μmol·L-1) Uric acid/(μmol·L-1) 326.00(275.00, 378.00) 305.00(253.00, 363.00) 3.57 < 0.001
    血清骨钙素/(μg·L-1) Serum osteocalcin/(μg·L-1) 12.26(9.87, 15.85) 12.13(9.45, 15.75) 0.57 0.163
    糖化血红蛋白/% Glycosylated hemoglobin/% 8.40(7.00, 10.00) 9.10(7.40, 10.90) -3.99 < 0.001
    空腹血糖/(mmol·L-1) Fasting plasma glucose/(mmol·L-1) 7.76(6.39, 9.85) 8.10(6.78, 10.27) -2.85 0.004
    餐后2 h血糖/(mmol·L-1) 2-hour postprandial blood glucose/(mmol·L-1) 15.50(12.90, 18.40) 16.30(13.15, 19.65) -2.79 0.005
    空腹胰岛素/(μIU·mL-1) Fasting insulin/(μIU·mL-1) 6.69(4.90, 9.91) 6.69(3.66, 8.34) -4.16 < 0.001
    餐后2 h胰岛素/(μIU·mL-1) 2-hour post meal insulin/(μIU·mL-1) 26.22(15.00, 47.20) 24.10(12.05, 40.70) -2.02 < 0.001
    胰岛素抵抗指数Homeostasis model assessment insulin resistance 2.51(1.60, 3.86) 2.21(1.34, 3.52) -2.59 0.010
    胰岛素敏感指数Homeostasis model assessment insulin sensitivity 32.35(18.16, 58.85) 25.00(13.10, 45.35) -4.62 < 0.001
    C-反应蛋白/(mg·L-1) C-reactive protein/(mg·L-1) 2.50(1.70, 3.50) 2.50(1.70, 3.60) -0.27 0.784
    注:GLP-1,胰高糖素样肽-1; MCI, 轻度认知功能障碍。
    ①使用GLP-1药物指使用利拉鲁肽注射液、度拉糖肽注射液; ②以M(P25P75)或人数(占比/%)或x±s表示。
    Note: GLP-1, glucagon-like peptide-1; MCI, mild cognitive impairment.
    ① The use of GLP-1 drug refers to the use of liraglutide injection and dulaglutide injection; ② M(P25P75) or number of people (proportion/%) or x±s.
    下载: 导出CSV
  • [1] Li YZ, Teng D, Shi XG, et al. Prevalence of diabetes recorded in mainland China using 2018 diagnostic criteria from the American Diabetes Association: national cross sectional study[J]. BMJ, 2020, 369: m997. DOI: 10.1136/bmj.m997.
    [2] Meyhöfer S, Schmid SM. Diabetes complications - diabetes and the nervous system[J]. Dtsch Med Wochenschr, 2020, 145(22): 1599-1605. DOI: 10.1055/a-1038-0102.
    [3] Livingston G, Huntley J, Sommerlad A, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission[J]. Lancet, 2020, 396(10248): 413-446. DOI: 10.1016/S0140-6736(20)30367-6.
    [4] You Y, Liu ZZ, Chen YN, et al. The prevalence of mild cognitive impairment in type 2 diabetes mellitus patients: a systematic review and meta-analysis[J]. Acta Diabetol, 2021, 58(6): 671-685. DOI: 10.1007/s00592-020-01648-9.
    [5] 黄倩, 杜蕾, 昌菁, 等. 中青年2型糖尿病患者并发轻度认知功能障碍相关影响因素研究[J]. 现代生物医学进展, 2021, 21(22): 4256-4261. DOI: 10.13241/j.cnki.pmb.2021.22.011.

    Huang Q, Du L, Chang J, et al. Related factors of mild cognitive impairment in young and middle-aged patients with type 2 diabetes mellitus[J]. Prog Mod Biomed, 2021, 21(22): 4256-4261. DOI: 10.13241/j.cnki.pmb.2021.22.011.
    [6] 陈新宇, 周军良, 李婷婷, 等. 基于随机森林算法和Logistic回归分析的老年肌肉衰减症影响因素[J]. 中华疾病控制杂志, 2022, 26(3): 357-361. DOI: 10.16462/j.cnki.zhjbkz.2022.03.020.

    Chen XY, Zhou JL, Li TT, et al. Influential factors of sarcopenia in older adults based on random forest and Logistic regression[J]. Chin J Dis Control Prev, 2022, 26(3): 357-361. DOI: 10.16462/j.cnki.zhjbkz.2022.03.020.
    [7] 张玮畅, 田晶, 杨弘, 等. 冠心病合并慢性心力衰竭患者5年全因死亡生存分析与可解释性研究[J]. 中华疾病控制杂志, 2023, 27(4): 373-378, 391. DOI: 10.16462/j.cnki.zhjbkz.2023.04.001.

    Zhang WC, Tian J, Yang H, et al. 5-year all-cause mortality survival analysis and interpretable study in patients with coronary artery disease combined with chronic heart failure[J]. Chin J Dis Control Prev, 2023, 27(4): 373-378, 391. DOI: 10.16462/j.cnki.zhjbkz.2023.04.001.
    [8] 中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2020年版)(上)[J]. 中国实用内科杂志, 2021, 41(8): 668-695. DOI: 10.19538/j.nk2021080106.

    Chinese Diabetes Society. Guidelines for prevention and treatment of type 2 diabetes in China (2020 edition) (Ⅰ)[J]. Chin J Pract Intern Med, 2021, 41(8): 668-695. DOI: 10.19538/j.nk2021080106.
    [9] 李岚. 常用认知障碍评估工具的特点与适用性[J]. 上海护理, 2022, 22(3): 73-75. DOI: 10.3969/j.issn.1009-8399.2022.03.017.

    Li L. Characteristics and suitability of common cognitive impairment assessment tools[J]. Shanghai Nurs, 2022, 22(3): 73-75. DOI: 10.3969/j.issn.1009-8399.2022.03.017.
    [10] Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment[J]. J Am Geriatr Soc, 2005, 53(4): 695-699. DOI: 10.1111/j.1532-5415.2005.53221.x.
    [11] Pinto TCC, Machado L, Bulgacov TM, et al. Is the montreal cognitive assessment (MoCA) screening superior to the mini-mental state examination (MMSE) in the detection of mild cognitive impairment (MCI) and Alzheimer's Disease (AD) in the elderly?[J]. Int Psychogeriatr, 2019, 31(4): 491-504. DOI: 10.1017/S1041610218001370.
    [12] Li J, Zhang WY, Wang X, et al. Functional magnetic resonance imaging reveals differences in brain activation in response to thermal stimuli in diabetic patients with and without diabetic peripheral neuropathy[J]. PLoS One, 2018, 13(1): e0190699. DOI: 10.1371/journal.pone.0190699.
    [13] 徐爱红, 李海平, 苏婷婷, 等. 老年骨质疏松症患者的认知功能特点及相关性[J]. 临床与病理杂志, 2022, 42(5): 1130-1135. DOI: 10.3978/j.issn.2095-6959.2022.05.018.

    Xu AH, Li HP, Su TT, et al. Characteristics and correlation of cognitive function in elderly patients with osteoporosis[J]. Int J Pathol Clin Med, 2022, 42(5): 1130-1135. DOI: 10.3978/j.issn.2095-6959.2022.05.018.
    [14] 薛承浩, 郭海健, 李明码, 等. 2型糖尿病患者轻度认知功能障碍影响因素的Meta分析[J]. 中国循证医学杂志, 2022, 22(5): 568-574. DOI: 10.7507/1672-2531.202111062.

    Xue CH, Guo HJ, Li MM, et al. Influencing factors of mild cognitive impairment in patients with type 2 diabetes: a meta-analysis[J]. Chin J Evid Based Med, 2022, 22(5): 568-574. DOI: 10.7507/1672-2531.202111062.
    [15] 李晶, 袁金环, 王猛, 等. 动脉硬化程度对糖尿病患者认知功能的影响研究[J]. 中国全科医学, 2020, 23(19): 2417-2422. DOI: 10.12114/j.issn.1007-9572.2019.00.688.

    Li J, Yuan JH, Wang M, et al. Impact of arterial stiffness level on cognitive function among diabetic patients[J]. Chin Gen Pract, 2020, 23(19): 2417-2422. DOI: 10.12114/j.issn.1007-9572.2019.00.688.
    [16] 姚瑶, 褚敏. 糖尿病肾病患者认知功能障碍与血清β淀粉样蛋白的关系[J]. 临床荟萃, 2022, 37(9): 813-816. DOI: 10.3969/j.issn.1004-583X.2022.09.009.

    Yao Y, Chu M. Relationship between serum amyloid β-protein and cognitive dysfunction in patients with diabetic kidney disease[J]. Clin Focus, 2022, 37(9): 813-816. DOI: 10.3969/j.issn.1004-583X.2022.09.009.
    [17] 刘晶晶, 李楠楠. 高龄老人体位性低血压对轻度认知功能障碍的影响[J]. 中国实用内科杂志, 2021, 41(4): 315-320. DOI: 10.19538/j.nk2021040111.

    Liu JJ, Li NN. Effect of postural hypotension on mild cognitive impairment in the elderly[J]. Chin J Pract Intern Med, 2021, 41(4): 315-320. DOI: 10.19538/j.nk2021040111.
    [18] Ehtewish H, Arredouani A, El-Agnaf O. Diagnostic, prognostic, and mechanistic biomarkers of diabetes mellitus-associated cognitive decline[J]. Int J Mol Sci, 2022, 23(11): 6144. DOI: 10.3390/ijms23116144.
    [19] 冯莓婷, 刘佳昊, 王晓丽. 血清25-羟维生素D、同型半胱氨酸、尿酸水平与老年高血压患者发生轻度认知功能障碍的相关性[J]. 江苏大学学报(医学版), 2023, 33(3): 252-257, 264. DOI: 10.13312/j.issn.1671-7783.y220276.

    Feng MT, Liu JH, Wang XL. Relationship between serum 25-hydroxyvitamin D, homocysteine, uric acid and mild cognitive impairment in elderly patients with hypertension[J]. J Jiangsu Univ (Med Ed), 2023, 33(3): 252-257, 264. DOI: 10.13312/j.issn.1671-7783.y220276.
  • 加载中
图(6) / 表(1)
计量
  • 文章访问数:  153
  • HTML全文浏览量:  26
  • PDF下载量:  55
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-05-27
  • 修回日期:  2023-09-04
  • 网络出版日期:  2024-04-08
  • 刊出日期:  2024-03-10

目录

    /

    返回文章
    返回