急性加重性慢性阻塞性肺疾病低钠血症风险因素分析及预测模型构建

    Analysis of the risk factors and construction of prediction model of hyponatremia in acute exacerbation of chronic obstructive pulmonary disease

    • 摘要: 目的: 分析慢性阻塞性肺疾病急性加重期(AECOPD)病人发生低钠血症风险因素,并构建预测低钠血症风险的动态列线图。方法: 分析224例AECOPD病人,通过Boruta算法筛选低钠血症重要风险因素。采用受试者工作特征(ROC)曲线分析变量曲线下面积(AUC)。基于风险因素构建AECOPD病人发生低钠血症风险的列线图;使用内部数据集评估列线图预测性能。使用DynNom包将列线图发布至网络中构建AECOPD病人发生低钠血症风险的动态列线图。结果: 224例中50例出现低钠血症,发生率为22.3%。Boruta算法发现白蛋白(ALB)、体质量指数(BMI)、红细胞沉降率(ESR)、2型糖尿病(T2DM)、C反应蛋白(CRP)、血糖(FBG)、肌酐(Cr)是AECOPD病人发生低钠血症的独立风险因素。ALB、BMI、ESR、T2DM、CRP、FBG和Cr诊断低钠血症AUC值分别为0.759(0.698~0.814)、0.772(0.712~0.826)、0.689(0.624~0.749)、0.625(0.558~0.689)、0.503(0.435~0.570)、0.574(0.506~0.639)、0.516(0.448~0.583)。构建AECOPD病人发生低钠血症的列线图模型,校正曲线预测值和实际值具有较好的一致性,决策曲线显示阈值概率为2.7%~100%时,列线图预测AECOPD病人发生低钠血症的净获益率较高。结论: ALB、BMI、ESR、T2DM、CPR、FBG、Cr是AECOPD病人发生低钠血症的独立危险因素,基于此构建AECOPD病人发生低钠血症的动态列线图预测模型有较好预测和临床使用价值。

       

      Abstract: Objective: To analyze the risk factors of hyponatremia in patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD) and construct a dynamic nomogram for predicting the risk of hyponatremia. Methods: A total of 224 patients with AECOPD were analyzed, and the Boruta algorithm was used to screen for important risk factors of hyponatremia.The area under the curve(AUC) of the variable was analyzed by using the receiver operating characteristic(ROC) curve.The nomogram of the risk of hyponatremia in AECOPD patients was constructed based on risk factors.The prediction performance of the nomogram was evaluated using internal datasets.The DynNom package was used to publish the nomogram to the network to construct a dynamic nomogram of the risk of hyponatremia in AECOPD patients. Results: Among the 224 cases, 50 cases developed hyponatremia, with an incidence rate of 22.3%.The Boruta algorithm found that the albumin(ALB), body mass index(BMI), erythrocyte sedimentation rate(ESR), type 2 diabetes mellitus(T2DM), C-reactive protein(CRP), blood glucose(FBG) and creatinine(Cr) were the independent risk factors of hyponatremia in patients with AECOPD.The AUC values of ALB, BMI, ESR, T2DM, CRP, FBG and Cr for diagnosing hyponatremia were 0.759(0.698-0.814), 0.772(0.712-0.826), 0.689(0.624-0.749), 0.625(0.558-0.689), and 0.503(0.435-0.570), 0.574(0.506-0.639), 0.516(0.448-0.583), respectively.A nomogram model for hyponatremia in patients with AECOPD was constructed.The predicted values of the correction curve and actual values showed good consistency.When the threshold probability of the decision curve was 2.7%-100%, the net benefit rate of nomogram in predicting hyponatremia in patients with AECOPD was relatively high. Conclusions: The ALB, BMI, ESR, T2DM, CPR, FBG, and Cr are the independent risk factors of hyponatremia in patients with AECOPD.Based on these factors, the constructed dynamic nomogram prediction model for hyponatremia in patients with AECOPD has good predictive and clinical application value.

       

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