Liver Cirrhosis Study Group, Department of Gastroenterology, General Hospital of Northern Theater Command (Teaching Hospital of Shenyang Pharmaceutical University), Shenyang, China.
Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, China.
Sci Rep. 2024 Nov 20;14(1):28719. doi: 10.1038/s41598-024-73256-4.
Hyponatremia can worsen the outcomes of patients with liver cirrhosis. However, it remains unclear about how to predict the risk of death in cirrhotic patients with hyponatremia. Patients with liver cirrhosis and hyponatremia were screened. Eligible patients were randomly divided into the training (n = 472) and validation (n = 471) cohorts. In the training cohort, the independent predictors for in-hospital death were identified by logistic regression analyses. Odds ratios (ORs) were calculated. An artificial neural network (ANN) model was established in the training cohort. Areas under curve (AUCs) of ANN model, Child-Pugh, model for end-stage liver disease (MELD), and MELD-Na scores were calculated by receiver operating characteristic curve analyses. In multivariate logistic regression analyses, ascites (OR = 2.705, P = 0.042), total bilirubin (OR = 1.004, P = 0.003), serum creatinine (OR = 1.004, P = 0.017), and international normalized ratio (OR = 1.457, P = 0.005) were independently associated with in-hospital death. Based on the four variables, an ANN model was established. Its AUC was 0.865 and 0.810 in the training and validation cohorts, respectively, which was significantly larger than those of Child-Pugh (AUC = 0.757), MELD (AUC = 0.765), and MELD-Na (AUC = 0.769) scores. An ANN model has been developed and validated for the prediction of in-hospital death in patients with liver cirrhosis and hyponatremia.
低钠血症可使肝硬化患者的预后恶化。然而，对于低钠血症的肝硬化患者如何预测死亡风险仍不清楚。筛选出肝硬化伴低钠血症的患者。将符合条件的患者随机分为训练组（n=472）和验证组（n=471）。在训练组中，通过逻辑回归分析确定住院死亡的独立预测因素。计算比值比（ORs）。在训练组中建立人工神经网络（ANN）模型。通过受试者工作特征曲线分析计算 ANN 模型、Child-Pugh、终末期肝病模型（MELD）和 MELD-Na 评分的曲线下面积（AUCs）。在多变量逻辑回归分析中，腹水（OR=2.705，P=0.042）、总胆红素（OR=1.004，P=0.003）、血清肌酐（OR=1.004，P=0.017）和国际标准化比值（OR=1.457，P=0.005）与住院期间死亡独立相关。基于这四个变量，建立了一个 ANN 模型。其在训练组和验证组中的 AUC 分别为 0.865 和 0.810，明显大于 Child-Pugh（AUC=0.757）、MELD（AUC=0.765）和 MELD-Na（AUC=0.769）评分。已经开发并验证了一种 ANN 模型，用于预测肝硬化伴低钠血症患者的住院期间死亡。
