Gastro Unit, Medical Division, Hvidovre University Hospital, Hvidovre, Denmark.
Novo Nordisk Foundation Centre for Protein Research, Copenhagen University, Copenhagen, Denmark.
Sci Rep. 2023 Nov 16;13(1):20039. doi: 10.1038/s41598-023-47384-2.
The inflammatory activity in cirrhosis is often pronounced and related to episodes of decompensation. Systemic markers of inflammation may contain prognostic information, and we investigated their possible correlation with admissions and mortality among patients with newly diagnosed liver cirrhosis. We collected plasma samples from 149 patients with newly diagnosed (within the past 6 months) cirrhosis, and registered deaths and hospital admissions within 180 days. Ninety-two inflammatory markers were quantified and correlated with clinical variables, mortality, and admissions. Prediction models were calculated by logistic regression. We compared the disease courses of our cohort with a validation cohort of 86 patients with cirrhosis. Twenty of 92 markers of inflammation correlated significantly with mortality within 180 days (q-values of 0.00-0.044), whereas we found no significant correlations with liver-related admissions. The logistic regression models yielded AUROCs of 0.73 to 0.79 for mortality and 0.61 to 0.73 for liver-related admissions, based on a variety of modalities (clinical variables, inflammatory markers, clinical scores, or combinations thereof). The models performed moderately well in the validation cohort and were better able to predict mortality than liver-related admissions. In conclusion, markers of inflammation can be used to predict 180-day mortality in patients with newly diagnosed cirrhosis. Prediction models for newly diagnosed cirrhotic patients need further validation before implementation in clinical practice.Trial registration: NCT04422223 (and NCT03443934 for the validation cohort), and Scientific Ethics Committee No.: H-19024348.
肝硬化的炎症活动通常很明显,与失代偿期发作有关。系统性炎症标志物可能包含预后信息,我们研究了它们与新诊断为肝硬化患者的住院和死亡的可能相关性。我们收集了 149 例新诊断(过去 6 个月内)肝硬化患者的血浆样本,并登记了 180 天内的死亡和住院情况。定量分析了 92 种炎症标志物,并将其与临床变量、死亡率和住院情况进行了相关性分析。通过逻辑回归计算了预测模型。我们将本队列的疾病过程与另一队列(86 例肝硬化患者)进行了比较。92 种炎症标志物中有 20 种与 180 天内的死亡率显著相关(q 值为 0.00-0.044),而与肝相关住院无显著相关性。基于多种方式(临床变量、炎症标志物、临床评分或其组合),逻辑回归模型得出的死亡率 AUROC 值为 0.73 至 0.79,肝相关住院 AUROC 值为 0.61 至 0.73。这些模型在验证队列中表现良好,能够更好地预测死亡率,而不是肝相关住院。总之,炎症标志物可用于预测新诊断为肝硬化患者的 180 天死亡率。在将预测模型用于临床实践之前,还需要对新诊断为肝硬化的患者进行进一步验证。试验注册:NCT04422223(验证队列为 NCT03443934),以及科学伦理委员会编号:H-19024348。