Wu Long, Yuan Zhiquan, Zeng Yuhong, Yang Lanqing, Hu Qin, Zhang Huan, Li Chengying, Chen Yanxiu, Zhang Zhihui, Zhong Li, Li Yafei, Wu Na
Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), PR China; Evidence-based Medicine and Clinical Epidemiology Center, Army Medical University (Third Military Medical University), PR China.
Department of Cardiology and the Center for Circadian Metabolism and Cardiovascular Disease, Southwest Hospital, Army Medical University (Third Military Medical University), PR China.
Clinics (Sao Paulo). 2025 Mar 11;80:100610. doi: 10.1016/j.clinsp.2025.100610. eCollection 2025.
This study aimed to assess the predictive value of 7 routinely available inflammation biomarkers for stroke and all-cause mortality in 229 non-valvular AF patients.
C-reactive protein, Albumin (ALB), d-dimer, fibrinogen, the number of platelets, lymphocytes, monocyte and neutrophils were measured. The Multivariable Cox proportional hazard model was used to assess the predictive value of the inflammation biomarkers for stroke and all-cause mortality, the c-statistic, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI) were calculated. Lymphocyte Monocyte Ratio (LMR) was the most informative biomarker for predicting stroke, and adding LMR to the CHADS-VASc score did not improve its predictive ability for stroke, but it did improve its reclassification ability. Similar results were observed when comparing LMR+ CHADS-VASc score with the ABC stroke score. For all-cause mortality, a Systemic Inflammation Score (SIS) score was calculated using ALB, fibrinogen and LMR, and adding SIS to the CHADS-VASc score showed a significant improvement in its predictive ability and reclassification ability. There were no significant differences in predictive and reclassification ability for all-cause mortality between SIS+CHADS-VASc score and ABC death score.
Adding routinely available inflammatory biomarkers to the CHADS-VASc score increased its ability to predict all-cause mortality, suggesting this cost-effective biomarker strategy may help to improve decision support in AF.
本研究旨在评估7种常规可用的炎症生物标志物对229例非瓣膜性房颤患者中风及全因死亡率的预测价值。
检测了C反应蛋白、白蛋白（ALB）、D-二聚体、纤维蛋白原、血小板、淋巴细胞、单核细胞及中性粒细胞数量。采用多变量Cox比例风险模型评估炎症生物标志物对中风及全因死亡率的预测价值，并计算c统计量、净重新分类改善（NRI）和综合判别改善（IDI）。淋巴细胞单核细胞比值（LMR）是预测中风最具信息量的生物标志物，将LMR加入CHADS-VASc评分并未提高其对中风的预测能力，但提高了其重新分类能力。将LMR+CHADS-VASc评分与ABC中风评分进行比较时观察到类似结果。对于全因死亡率，使用ALB、纤维蛋白原和LMR计算全身炎症评分（SIS），将SIS加入CHADS-VASc评分显示其预测能力和重新分类能力有显著提高。SIS+CHADS-VASc评分与ABC死亡评分在全因死亡率的预测和重新分类能力方面无显著差异。
将常规可用的炎症生物标志物加入CHADS-VASc评分可提高其预测全因死亡率的能力，表明这种具有成本效益的生物标志物策略可能有助于改善房颤的决策支持。
