Alkaline Phosphatase to Albumin Ratio as a Novel Predictor of All-Cause Mortality in Critically Ill Patients With Atrial Fibrillation

碱性磷酸酶与白蛋白比值作为房颤危重患者全因死亡率的新型预测指标

阅读:1

Abstract

BACKGROUND: Alkaline phosphatase to albumin ratio (APAR) is an emerging prognostic indicator for sepsis, cancer, and coronary artery disease. However, the predictive value of APAR in patients with atrial fibrillation (AF) has not been investigated yet. Therefore, this study aims to explore the association between APAR and the risk of mortality in critically ill patients with AF. METHODS: The data of AF patients were extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. Patients with AF were divided into three groups according to the APAR tertiles. Study outcomes were defined as 28-day and 365-day all-cause mortality. The Kaplan-Meier analysis was conducted to compare the survival rates between groups. Cox proportional hazards regression and restricted cubic spline (RCS) were used to investigate the association between APAR and all-cause mortality. Receiver operating characteristic (ROC) curve analysis was utilized to evaluate the predictive value of APAR for study outcomes. RESULTS: A total of 1105 critically ill patients with AF were enrolled in the study. The Kaplan-Meier analysis demonstrated that patients with the highest APAR had the lowest survival rate. The Cox regression analysis indicated that the highest APAR tertile was significantly associated with 28-day (HR, 1.64 [95% CI 1.20-2.25]; p=0.002) and 365-day (HR, 1.87 [95% CI 1.47-2.39]; p < 0.001) all-cause mortality. Nonlinear relationships between APAR and 28-day and 365-day all-cause mortality were illustrated based on the RCS curves. The areas under the ROC curves for predicting 28-day and 365-day all-cause mortality were 0.617 and 0.642, respectively. CONCLUSIONS: Our research suggested that APAR was a simple biomarker for the prognosis in patients with AF.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。