摘要目的:探讨血清学指标对代偿期肝硬化轻微型肝性脑病（MHE）的诊断价值，构建基于血清学指标的联合模型并评估其对MHE的诊断价值。方法:前瞻性、多中心研究。选取2021年10月至2022年8月来自我国15个省（自治区、直辖市）的23家医院就诊的代偿期肝硬化患者263例。收集患者临床资料及实验室检查结果，并计算终末期肝病模型（MELD）评分。使用基线血氨测量值/正常参考值上限（AMM-ULN）集中校正各中心血氨测量结果，以我国《肝硬化肝性脑病诊疗指南》标准，数字连接试验-A、数字符号试验均异常作为诊断MHE的标准。基于R语言caret包将患者随机（7∶3）分为训练集（ n=185）和验证集（ n=78）。通过Logistic回归构建诊断MHE的联合模型；受试者工作特征曲线下面积（AUC）、Hosmer-Lemeshow拟合优度检验及校准曲线图评估诊断性能，并用Bootstrap法（ n=200）进行内部验证；Delong检验比较AUC之间的差异。 结果:训练集中，MHE占37.8%（70/185），MHE组AMM-ULN、白蛋白、血小板、碱性磷酸酶、国际标准化比值、终末期肝病模型评分以及教育年限与无MHE组比较，差异有统计学意义（ P均<0.05）。多因素Logistic回归分析显示，AMM-ULN（ OR=1.78，95% CI 1.05~3.14， P=0.038）和MELD评分（ OR=1.11，95% CI 1.04~1.20， P=0.002）是MHE的独立危险因素，AUC分别为0.663和0.625。联合AMM-ULN、MELD评分和教育年限的联合模型诊断MHE的AUC为0.755，特异度和敏感度分别为85.2%和55.7%。Hosmer-Lemeshow拟合优度检验表明模型具有较好的校准度（ P=0.733），联合模型内部验证AUC为0.752。Delong检验显示联合模型诊断效能优于单独使用血氨（ P=0.020）和MELD评分（ P=0.003）。验证集中，联合模型诊断MHE的AUC为0.794，Hosmer-Lemeshow拟合优度检验显示有较好的校准度（ P=0.841）。 结论:基于AMM-ULN、MELD评分和教育年限的联合模型可提高对MHE的诊断价值。

abstractsObjective:To investigate the diagnostic accuracy of serological indicators and evaluate the diagnostic value of a new established combined serological model on identifying the minimal hepatic encephalopathy (MHE) in patients with compensated cirrhosis.Methods:This prospective multicenter study enrolled 263 compensated cirrhotic patients from 23 hospitals in 15 provinces, autonomous regions and municipalities of China between October 2021 and August 2022. Clinical data and laboratory test results were collected, and the model for end-stage liver disease (MELD) score was calculated. Ammonia level was corrected to the upper limit of normal (AMM-ULN) by the baseline blood ammonia measurements/upper limit of the normal reference value. MHE was diagnosed by combined abnormal number connection test-A and abnormal digit symbol test as suggested by Guidelines on the management of hepatic encephalopathy in cirrhosis. The patients were randomly divided (7∶3) into training set ( n=185) and validation set ( n=78) based on caret package of R language. Logistic regression was used to establish a combined model of MHE diagnosis. The diagnostic performance was evaluated by the area under the curve (AUC) of receiver operating characteristic curve, Hosmer-Lemeshow test and calibration curve. The internal verification was carried out by the Bootstrap method ( n=200). AUC comparisons were achieved using the Delong test. Results:In the training set, prevalence of MHE was 37.8% (70/185). There were statistically significant differences in AMM-ULN, albumin, platelet, alkaline phosphatase, international normalized ratio, MELD score and education between non-MHE group and MHE group (all P<0.05). Multivariate Logistic regression analysis showed that AMM-ULN [odds ratio ( OR)=1.78, 95% confidence interval ( CI) 1.05-3.14, P=0.038] and MELD score ( OR=1.11, 95% CI 1.04-1.20, P=0.002) were independent risk factors for MHE, and the AUC for predicting MHE were 0.663, 0.625, respectively. Compared with the use of blood AMM-ULN and MELD score alone, the AUC of the combined model of AMM-ULN, MELD score and education exhibited better predictive performance in determining the presence of MHE was 0.755, the specificity and sensitivity was 85.2% and 55.7%, respectively. Hosmer-Lemeshow test and calibration curve showed that the model had good calibration ( P=0.733). The AUC for internal validation of the combined model for diagnosing MHE was 0.752. In the validation set, the AUC of the combined model for diagnosing MHE was 0.794, and Hosmer-Lemeshow test showed good calibration ( P=0.841). Conclusion:Use of the combined model including AMM-ULN, MELD score and education could improve the predictive efficiency of MHE among patients with compensated cirrhosis.