Song Ya-Qi, Fu Xin-Yu, Yan Si-Yan, Qi Rong-Bin, Zhou Yi-Jing, Liang Jia-Wei, Zhang Jin-Qiu, Ye Li-Ping, Mao Xin-Li, Li Shao-Wei
Department of Gastroenterology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, People's Republic of China.
Department of Gastroenterology, Taizhou Hospital of Zhejiang Province, Linhai, Zhejiang, People's Republic of China.
Int J Gen Med. 2025 Feb 7;18:643-658. doi: 10.2147/IJGM.S490328. eCollection 2025.
Acute-on-chronic liver failure (ACLF) is a rapidly progressive and highly fatal condition. Early identification of critically ill patients is crucial. Hepatitis B virus-related ACLF (HBV-ACLF), the main cause of ACLF in China, is characterized by liver failure and coagulation dysfunction. Dynamic changes in total bilirubin (TB) and international normalized ratio (INR) can reflect disease progression. This study aims to investigate the clinical application of dynamic trajectories of TB and INR in HBV-ACLF patients.
Retrospective data from 194 patients at Taizhou Hospital, China (Jan 2012 - June 2023), meeting COSSH-ACLF criteria, were analyzed. A latent class mixed model (LCMM) identified three trajectory groups (declining, stable, fluctuating) based on bilirubin and INR changes. Clinical applicability of these groups was investigated.
The 194 patients were divided into the trajectory groups mentioned above. The declining group had lower predicted scores and a better prognosis. The stable and fluctuating groups had worse prognosis compared to the declining group (P<0.001). Artificial liver support did not improve short-term prognosis for the stable group; instead, it was a risk factor (OR 2.16, 95% CI [0.23-3.79], P=0.007). Subgroup analysis showed no interaction between predictive models and trajectory groups. Additionally, trajectory grouping improved the predictive effectiveness of existing models.
Based on our trajectory analysis, patients with a continuous declining in bilirubin and INR values showed the best prognosis, highlighting the clinical significance of trajectory grouping in treatment decisions. Trajectory grouping can complement existing scoring models, improving predictive effectiveness.
慢加急性肝衰竭(ACLF)是一种进展迅速且致死率高的疾病。早期识别重症患者至关重要。乙型肝炎病毒相关慢加急性肝衰竭(HBV-ACLF)是中国ACLF的主要病因,其特征为肝衰竭和凝血功能障碍。总胆红素(TB)和国际标准化比值(INR)的动态变化可反映疾病进展。本研究旨在探讨TB和INR动态轨迹在HBV-ACLF患者中的临床应用。
分析了中国台州医院194例(2012年1月至2023年6月)符合COSSH-ACLF标准患者的回顾性数据。基于胆红素和INR变化,采用潜在类别混合模型(LCMM)识别出三个轨迹组(下降、稳定、波动)。对这些组的临床适用性进行了研究。
194例患者被分为上述轨迹组。下降组的预测评分较低,预后较好。与下降组相比,稳定组和波动组的预后较差(P<0.001)。人工肝支持并不能改善稳定组的短期预后;相反,它是一个危险因素(OR 2.16,95%CI[0.23-3.79],P=0.007)。亚组分析显示预测模型与轨迹组之间无相互作用。此外,轨迹分组提高了现有模型的预测有效性。
基于我们的轨迹分析,胆红素和INR值持续下降的患者预后最佳,突出了轨迹分组在治疗决策中的临床意义。轨迹分组可补充现有评分模型,提高预测有效性。