基于RFH-NPT及SII评分构建列线图模型预测肝硬化肌少症的临床价值

摘要/Abstract

摘要： 目的基于RFH-NPT及SII评分构建列线图模型,探讨其预测肝硬化肌少症的临床应用价值。方法选取2021年6月至2023年6月在我院住院的肝硬化患者125例作为研究对象,采用第三腰椎骨骼肌质量指数作为肌少症诊断依据,将其分为肌少症组(36例)和非肌少症组(89例),采用RFH-NPT、SII评分进行营养不良-炎症评估。根据多因素logistic回归结果建立列线图模型。采用Bootstrap法对该模型进行内部验证,并采用C-index评价模型的区分度,校准曲线评价模型的校准度。结果肝硬化肌少症组年龄为(65.4±4.2)岁,非肌少症组年龄为(51.2±4.0)岁,(t=6.321,P<0.001);肌少症组白蛋白为(27.16±4.56)g/L,非肌少症组为(33.48±4.92)g/L,(t=-3.998,P<0.001);肌少症组胆红素为(37.34±12.42)μmol/L,非肌少症组为(25.41±10.17)μmol/L,(t=2.865,P=0.046);肌少症组RFH-NPT评分＜1分11例(30.56%),非肌少症组＜1分49例(55.06%),(χ²=6.346,P=0.013),肌少症SII评分为(406.22±79.46)分,非肌少症组评分为(312.36±61.71)分,(χ²=8.362,P<0.001),肌少症组合并腹腔积液29例(80.56%),非肌少症组合并腹腔积液32例(35.95%),(χ²=5.386,P=0.025);肌少症组合并肝性脑病8例(22.22%),非肌少症组合并腹腔积液9例(10.12%),(χ²=4.571,P=0.046)。多因素logstic回归分析结果显示,年龄(OR=1.423,95%CI=1.211~1.690)、白蛋白(OR=1.701,95%CI=1.346~2.543)、合并腹腔积液(OR=1.654,95%CI=1.192~2.339)、RFH-NPT评分(OR=2.233,95%CI=1.235~3.242)及SII评分(OR=2.001,95%CI=1.117~2.889)是影响肝硬化患者发生肌少症的独立危险因素(P<0.05)。据此构建的列线图预测模型采用Bootstrap内部验证,发现该模型具有良好的精准度和区分度,C-index指数为0.828( 95%CI为0.736~0.885),ROC曲线下面积(AUC)为0.838(95%CI:0.744~0.913)。结论 RFH-NPT评分、SII指数升高是肝硬化患者发生肌少症的独立危险因素,基于独立影响因素建立的列线图预测模型能够提高对肝硬化患者并发肌少症的预测效能。

关键词: 肝硬化, 肌少症, 皇家自由医院营养优先工具, 系统免疫炎症指数, 预测模型

Abstract: Objective To explore the clinical application value of nomogram model based on The Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) and Systemic Immune-Inflammation Index (SII) in predicting sarcopenia in liver cirrhotic patients. Methods A total of 125 patients with liver cirrhosis hospitalized in the Department of Nephrology, Jinan Eighth People′s Hospital from June 2021 to June 2023 were selected as the observation group. Using the third lumbar skeletal muscle mass index for the diagnosis of sarcopenia, the patients were divided into a sarcopenic group (n=36) and a non-sarcopenic group (n=89), RFH-NPT and SII scores were used to assess malnutrition-inflammation. A nomogram model was developed from the results of multivariate Logistic regression. The nomogram model was internally validated by Bootstrap method, and the discriminatory ability was evaluated by C-index.The calibration curve was used to evaluate the calibration degree of the nomogram model. Results Among the 125 patients with liver cirrhosis, 36(28.8%) were diagnosed with sarcopenia. The average ages of the patients in sarcopenia group and non-sarcopenic group were (65.4±4.2) and (51.2±4.00) respectively, t=6.321, P<0.001; The albumin level in sarcopenia group and non-sarcopenic group were (27.16±4.56) g/L and (33.48±4.92)g/L, t=-3.998, P<0.001; The bilirubin level in sarcopenia group and non-sarcopenic group were (37.34±12.42)μmol/L and (25.41±10.17μmol/L, respectively, t=2.865, P=0.046, RFH-NPT score in sarcopenia group and non-sarcopenic group were 11(30.56%)and 49(55.06%), χ²=3.349, P<0.001;SII score in sarcopenia group and non-sarcopenic group were (406.22±79.46) and (312.36±61.71), respectively, t=8.362, P<0.001; There were 29(80.56%)and 32(35.95%) patients with ascites in sarcopenia group and non-sarcopenic group, respectively, χ²=5.386, P=0.025; There were 8(22.22%) and 9(10.12%) patients with hepatic encephalopathy in sarcopenia group and non-sarcopenic group, χ²=4.571, P=0.046. The results of the multivariate Logstic regression analysis showed that, Age (OR=1.423,95%CI:1.211~1.690), albumin (OR=1.701,95%CI:1.346~2.543), combined intraperitoneal effusion (OR=1.654,95%CI=1.192~2.339), RFH-NPTscore (OR=2.233, 95%CI:1.235~3.242) and SII score (OR=2.001, 95%CI:1.117~2.889) was an independent risk factor affecting the development of sarcopenia in patients with cirrhosis (P<0.05). The nomogram prediction model was constructed by Bootstrap internal validation and found good accuracy and discrimination, with C-index of 0.828 (95%CI: 0.736~0.885) and area under ROC curve (AUC) of 0.838 (95%CI: 0.744~0.913). Conclusion Elevated RFH-NPT, SII scores are independent risk factors for sarcopenia in liver cirrhotic patients, and the nomogram prediction model based on independent influencing factors can improve the predictive efficacy of concurrent sarcopenia in patients with cirrhosis.

Key words: Cirrhosis, Sarcopenia, RFH-NPT, SII, Predictive model

张修振, 陈玲, 陈成武. 基于RFH-NPT及SII评分构建列线图模型预测肝硬化肌少症的临床价值[J]. 肝脏, 2026, 31(1): 39-43.

ZHANG Xiu-zhen,CHEN Ling,CHEN Cheng-wu. The clinical value of nomogram model based on RFH-NPT and SII score in predicting sarcopenia in liver cirrhotic patients[J]. Chinese Hepatolgy, 2026, 31(1): 39-43.

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