Li Dan, He Wu, Yu Bo, Wang Dao Wen, Ni Li
Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095# Jiefang Ave., Wuhan, 430030, China.
Sci Rep. 2024 Mar 11;14(1):5906. doi: 10.1038/s41598-024-56329-2.
Despite the progressive decline in the virulence of the novel coronavirus, there has been no corresponding reduction in its associated hospital mortality. Our aim was to redefine an accurate predictor of mortality risk in COVID-19 patients, enabling effective management and resource allocation. We conducted a retrospective analysis of 2917 adult Chinese patients diagnosed with COVID-19 who were admitted to our hospital during two waves of epidemics, involving the Beta and Omicron variants. Upon admission, NT-proBNP levels were measured, and we collected demographic, clinical, and laboratory data. We introduced a new concept called the NT-proBNP ratio, which measures the NT-proBNP level relative to age-specific maximum normal values. The primary outcome was all-cause in-hospital mortality. Our analysis revealed a higher in-hospital mortality rate in 2022, as shown by the Kaplan-Meier Survival Curve. To assess the predictive value of the NT-proBNP ratio, we employed the time-dependent receiver operating characteristic (ROC) curve. Notably, the NT-proBNP ratio emerged as the strongest predictor of mortality in adult Chinese hospitalized COVID-19 patients (area under the curve, AUC = 0.826; adjusted hazard ratio [HR], 3.959; 95% confidence interval [CI] 3.001-5.221; P < 0.001). This finding consistently held true for both the 2020 and 2022 subgroups. The NT-proBNP ratio demonstrates potential predictive capability compared to several established risk factors, including NT-proBNP, hsCRP, and neutrophil-to-lymphocyte ratio, when it comes to forecasting in-hospital mortality among adult Chinese patients with COVID-19.Trial registration Clinical Trial Registration: www.clinicaltrials.gov NCT05615792.
尽管新型冠状病毒的毒力在逐渐下降,但其相关的医院死亡率却没有相应降低。我们的目的是重新定义一种准确的预测新冠病毒疾病(COVID-19)患者死亡风险的指标,以实现有效的管理和资源分配。我们对2917名成年中国COVID-19患者进行了回顾性分析,这些患者在两波疫情期间(涉及贝塔和奥密克戎变种)入住我院。入院时,测量了N末端B型利钠肽原(NT-proBNP)水平,并收集了人口统计学、临床和实验室数据。我们引入了一个名为NT-proBNP比值的新概念,该比值衡量NT-proBNP水平相对于特定年龄的最大正常值。主要结局是全因院内死亡率。我们的分析显示,2022年的院内死亡率较高,如Kaplan-Meier生存曲线所示。为了评估NT-proBNP比值的预测价值,我们采用了时间依赖性受试者工作特征(ROC)曲线。值得注意的是,NT-proBNP比值是成年中国住院COVID-19患者死亡率的最强预测指标(曲线下面积,AUC = 0.826;调整后的风险比[HR],3.959;95%置信区间[CI] 3.001 - 5.221;P < 0.001)。这一发现对于2020年和2022年的亚组均一致成立。在预测成年中国COVID-19患者的院内死亡率方面,与包括NT-proBNP、超敏C反应蛋白(hsCRP)和中性粒细胞与淋巴细胞比值在内的几个既定风险因素相比,NT-proBNP比值显示出潜在的预测能力。试验注册 临床试验注册:www.clinicaltrials.gov NCT05615792。