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慢性肾脏病左心室肥厚的风险因素及其预测模型的构建

肖芝梅 丁晨慧 骆臣 钱蕾蕾

肖芝梅, 丁晨慧, 骆臣, 钱蕾蕾. 慢性肾脏病左心室肥厚的风险因素及其预测模型的构建[J]. 中华全科医学, 2024, 22(8): 1354-1358. doi: 10.16766/j.cnki.issn.1674-4152.003635
引用本文: 肖芝梅, 丁晨慧, 骆臣, 钱蕾蕾. 慢性肾脏病左心室肥厚的风险因素及其预测模型的构建[J]. 中华全科医学, 2024, 22(8): 1354-1358. doi: 10.16766/j.cnki.issn.1674-4152.003635
XIAO Zhimei, DING Chenhui, LUO Chen, QIAN Leilei. Risk factors of left ventricular hypertrophy for chronic kidney disease patients and construction of a predictive model[J]. Chinese Journal of General Practice, 2024, 22(8): 1354-1358. doi: 10.16766/j.cnki.issn.1674-4152.003635
Citation: XIAO Zhimei, DING Chenhui, LUO Chen, QIAN Leilei. Risk factors of left ventricular hypertrophy for chronic kidney disease patients and construction of a predictive model[J]. Chinese Journal of General Practice, 2024, 22(8): 1354-1358. doi: 10.16766/j.cnki.issn.1674-4152.003635

慢性肾脏病左心室肥厚的风险因素及其预测模型的构建

doi: 10.16766/j.cnki.issn.1674-4152.003635
基金项目: 

江苏省2019年高层次卫生人才“六个一工程”拔尖人才科研项目 LGY201926

南通市卫生健康委科研课题 QA2020051

详细信息
    通讯作者:

    钱蕾蕾,E-mail:ntsqll@163.com

  • 中图分类号: R692;R542.2

Risk factors of left ventricular hypertrophy for chronic kidney disease patients and construction of a predictive model

  • 摘要:   目的  构建慢性肾脏病(CKD)患者左心室肥厚(LVH)的风险预测模型,评价其临床应用价值。  方法  收集2018年1月—2022年8月间南通大学附属如皋医院收治的302例CKD Ⅲ~Ⅴ期患者的临床资料, 将患者按随机数字表法分为建模组(200例)与验证组(102例)。采用logistic回归分析研究LVH的危险因素并构建列线图模型,通过受试者工作特征曲线与校正曲线评价模型的预测能力。  结果  CKD患者LVH发生率为37.4%(113/302)。高龄(OR=1.054,95% CI: 1.020~1.089, P=0.002)、心血管病史(OR=5.826,95% CI: 2.263~15.003, P < 0.001)、CKD Ⅴ期(OR=5.831, 95% CI: 2.142~15.873, P=0.009)、收缩压升高(OR=1.019, 95% CI: 1.002~1.036, P=0.025)和高血磷(OR=1.109, 95% CI: 1.029~1.195, P=0.007)均是LVH的独立风险因素。基于上述因素构建预测模型,建模组与验证组AUC分别为0.850(95% CI: 0.796~0.904)和0.792(95% CI: 0.707~0.877)。校正曲线显示模型对LVH具有较好的预测能力。  结论  基于年龄、心血管疾病史、CKD分期、收缩压和血磷的列线图模型为识别高LVH风险的CKD患者提供了一项简便、有效的工具。

     

  • 图  1  慢性肾脏病LVH的预测列线图模型

    Figure  1.  Predictive nomogram model of LVH in chronic kidney disease patients

    图  2  列线图模型预测LVH的ROC曲线

    Figure  2.  ROC curves of the nomogram model for predicting LVH

    图  3  列线图模型预测LVH的校正曲线

    注:A为建模组,B为验证组。

    Figure  3.  Calibration curves of the nomogram model for predicting LVH

    表  1  建模组和验证组慢性肾脏疾病患者基线资料比较

    Table  1.   Comparisons of baseline characteristics of chronic kidney disease patients between the modeling group and the validation group

    基线特征 总计(n=302) 建模组(n=200) 验证组(n=102) 统计量 P
    年龄(x±s, 岁) 57.4±11.6 57.9±11.7 56.5±11.2 0.998a 0.319
    性别[例(%)] 1.136b 0.286
      女性 141(46.7) 89(44.5) 52(51.0)
      男性 161(53.3) 111(55.5) 50(49.0)
    BMI(x±s) 22.9±2.6 23.1±2.6 22.6±2.4 1.621a 0.106
    基础疾病[例(%)]
      糖尿病 139(46.0) 95(47.5) 44(43.1) 0.518b 0.472
      高血压 86(28.5) 57(28.5) 29(28.4) 0.001b 0.990
      COPD 47(15.6) 30(15.0) 17(16.7) 0.143b 0.706
    CKD分期[例(%)] 0.800b 0.670
      Ⅲ 181(59.9) 120(60.0) 61(59.8)
      Ⅳ 76(25.2) 48(24.0) 28(27.5)
      Ⅴ 45(14.9) 32(16.0) 13(12.7)
    eGFR[x±s,mL/(min·1.73 m2)] 32.6±14.6 31.9±15.1 33.8±13.5 0.390a 0.697
    SBP(x±s,mmHg) 134.4±21.2 135.3±22.6 132.5±18.0 1.087a 0.278
    DBP(x±s,mmHg) 81.8±11.2 81.7±11.7 82.1±10.4 0.291a 0.771
    尿白蛋白[M(P25, P75),g/24 h] 1.09(0.51,1.56) 1.22(0.60,1.56) 1.06(0.52,1.41) 1.632c 0.104
    血清白蛋白(x±s,g/L) 40.2±4.0 39.9±4.2 40.8±3.8 1.818a 0.070
    尿酸(x±s,mg/dL) 6.6±1.9 6.6±1.9 6.2±1.8 1.791a 0.079
    血红蛋白(x±s,g/L) 117.6±21.0 116.1±21.1 120.8±21.6 1.816a 0.070
    血清总胆固醇(x±s,mg/dL) 203.4±46.1 204.0±47.9 202.2±42.6 0.320a 0.749
    C反应蛋白(x±s,mg/L) 1.70±0.32 1.65±0.27 1.68±0.42 0.751a 0.453
    iPTH[M(P25, P75),pg/mL] 55.0(43.0,108.0) 54.0(43.0,103.0) 55.0(43.0,86.0) -0.680c 0.496
    血钙(x±s,mmol/L) 2.27±0.28 2.27±0.28 2.26±0.19 0.324a 0.746
    血磷[M(P25, P75),mmol/L] 1.20(1.02,1.44) 1.19(1.01,1.44) 1.20(1.03,1.45) 0.906c 0.366
    血钠(x±s,mmol/L) 136.2±4.9 135.9±5.0 136.8±4.8 1.499a 0.135
    血钾[M(P25, P75),mmol/L] 4.5(4.0,5.2) 4.5(4.0,5.1) 4.6(4.2,5.3) 0.972c 0.332
    LVH[例(%)] 0.044b 0.834
      否 189(62.6) 126(63.0) 63(61.8)
      是 113(37.4) 74(37.0) 39(38.2)
    注:at值,b为χ2值,cZ值。1 mmHg=0.133 kPa。
    下载: 导出CSV

    表  2  CKD患者LVH风险因素的logistic回归分析(建模组)

    Table  2.   Logistic regression analysis of risk factors for LVH in CKD patients (from the training group)

    变量 单因素logistic分析 多因素logistic分析
    OR(95% CI) P OR(95% CI) P
    年龄 1.073(1.042~1.105) < 0.001 1.054(1.020~1.089) 0.002
    性别(男性) 0.640(0.360~1.137) 0.128
    BMI 1.025(0.920~1.142) 0.653
    糖尿病史 0.863(0.487~1.529) 0.614
    心血管疾病史 5.261(2.327~11.893) < 0.001 5.826(2.263~15.003) < 0.001
    COPD 2.025(0.936~4.381) 0.073
    CKD分期
      Ⅳ期 2.093(1.031~4.246) 0.041 2.196(0.967~4.984) 0.060
      Ⅴ期 7.890(3.401~18.302) < 0.001 5.831(2.142~15.873) 0.009
    SBP 1.017(1.004~1.031) 0.010 1.019(1.002~1.036) 0.025
    DBP 0.991(0.956~1.016) 0.457
    尿白蛋白 0.912(0.659~1.261) 0.576
    血清白蛋白 0.422(0.206~0.863) 0.018 0.752(0.280~2.025) 0.573
    尿酸 1.072(0.921~1.246) 0.370
    血红蛋白 0.791(0.684~0.916) 0.002 0.916(0.742~1.130) 0.412
    血清总胆固醇 0.999(0.993~1.005) 0.771
    C反应蛋白 1.300(1.038~1.629) 0.022 1.047(0.777~1.411) 0.762
    iPTH 1.016(1.011~1.022) 0.007 1.024(0.898~1.168) 0.724
    血钙 0.838(0.356~1.970) 0.685
    血磷 1.128(1.054~1.208) < 0.001 1.109(1.029~1.195) 0.007
    血钠 1.092(0.806~1.479) 0.570
    血钾 1.008(0.998~1.018) 0.105
    注:变量赋值如下,性别(女性=0, 男性=1),糖尿病(否=0, 是=1),心血管疾病(否=0, 是=1),COPD(否=0, 是=1),CKD分期(Ⅲ期=1, Ⅳ期=2,Ⅴ期=3),其余变量均为连续型变量, 均以实际值赋值。
    下载: 导出CSV
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  • 收稿日期:  2023-09-25
  • 网络出版日期:  2024-11-19

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