Yuan Songsong, Taozhu Wen, Liu Juan, Zhang Wenfeng, Xu Qinglang, Zhu Ying, Xiang Tianxin, Wu Xiaoping
Jiangxi Medical Center for Critical Public Health Events, Jiangxi Provincial Key Laboratory of Prevention and Treatment of Infectious Diseases, The First Affiliated Hospital of Nanchang University, Nanchang, 330052, Jiangxi, People's Republic of China.
Department of Infectious Diseases, The First Affiliated Hospital of Nanchang University, Nanchang, China.
Sci Rep. 2025 Apr 24;15(1):14288. doi: 10.1038/s41598-025-91779-2.
Hepatitis B-related acute-on-chronic liver failure (HBV-ACLF) could result in disrupted glucose and lipid homeostasis, but its associations with ACLF is not fully defined. Here, we incorporated biomarkers associated with HBV-ACLF prognoses into a predictive nomogram, and examined its short- and long-term predictive capabilities. Eight hundred sixty-one HBV-ACLF, 20 healthy, and 54 chronic hepatitis B (CH) patients were recruited; the 4 characteristics most strongly associated with HBV-ACLF prognoses (age, glycosylated serum protein [GSP], high-density lipoprotein cholesterol [HDL-c], international normalized ratio), identified by logistic regression (uni-, multivariate) and machine-learning based analyses, were incorporated into the predictive nomogram. The nomogram was, under receiver operating characteristic and calibration curve analyses, highly accurate in identifying ACLF patients with worse prognoses after 28- and 90-days; it also demonstrated good clinical utility under decision curve analysis. Furthermore, higher GSP/HDL-c (GHR) was associated with worse ACLF prognoses, plus higher 28- and 90-day cumulative risk of death under Kaplan-Meier analysis. Therefore, the nomogram was able to accurately identify ACLF patients, who also had high GHR, at high risk for adverse prognosis; consequently, both glucose and lipid metabolism indicators are equally important for determining ACLF prognoses, and could serve as valuable early diagnostic tools for tailored ACLF interventions.
乙型肝炎相关慢加急性肝衰竭（HBV-ACLF）可导致糖脂稳态紊乱，但其与ACLF的关联尚未完全明确。在此，我们将与HBV-ACLF预后相关的生物标志物纳入预测列线图，并检验其短期和长期预测能力。招募了861例HBV-ACLF患者、20例健康人和54例慢性乙型肝炎（CH）患者；通过逻辑回归（单变量、多变量）和基于机器学习的分析确定的与HBV-ACLF预后最密切相关的4个特征（年龄、糖化血清蛋白[GSP]、高密度脂蛋白胆固醇[HDL-c]、国际标准化比值）被纳入预测列线图。在接受者操作特征和校准曲线分析中，该列线图在识别28天和90天后预后较差的ACLF患者方面具有高度准确性；在决策曲线分析中也显示出良好的临床实用性。此外，较高的GSP/HDL-c（GHR）与较差的ACLF预后相关，在Kaplan-Meier分析中28天和90天的累积死亡风险也较高。因此，该列线图能够准确识别GHR较高且预后不良风险较高的ACLF患者；因此，糖脂代谢指标对于确定ACLF预后同样重要，可作为有价值的早期诊断工具，用于定制ACLF干预措施。
