实用老年医学

实用老年医学 ›› 2025, Vol. 39 ›› Issue (8): 787-792.doi: 10.3969/j.issn.1003-9198.2025.08.007

• 临床研究 • 上一篇    下一篇

基于全身炎症反应指数的老年高尿酸血症病人全因及心血管病死亡风险预测模型构建

朱悦, 弓树娟, 郑莉, 张鸿鸿, 杨增奥, 吴正锋, 赵海静, 刘昱圻   

  1. 100853 北京市,中国人民解放军总医院第一医学中心(朱悦,张鸿鸿,吴正锋,赵海静);
    100039 北京市,中国人民解放军总医院第五医学中心肝病科(弓树娟);
    300071 天津市,南开大学医学院(郑莉);
    100041 北京市,中国人民解放军总医院第六医学中心心内科(杨增奥,刘昱圻)
  • 收稿日期:2025-01-16 出版日期:2025-08-20 发布日期:2025-08-19
  • 通讯作者: 刘昱圻,Email: ametuofo980869@163.com
  • 基金资助:
    国家自然科学基金资助项目(82070434/H0214)

Establishment of a predictive model for all-cause and cardiovascular mortality risk in elderly patients with hyperuricemia based on systemic inflammatory response index

ZHU Yue, GONG Shujuan, ZHENG Li, ZHANG Honghong, YANG Zeng’ao, WU Zhengfeng, ZHAO Haijing, LIU Yuqi   

  1. The First Medical Centre, Chinese PLA General Hospital, Beijing 100853, China(ZHU Yue, ZHANG Honghong, WU Zhengfeng, ZHAO Haijing);
    Department of Hepatology, the Fifth Medical Center, Chinese PLA General Hospital, Beijing 100039, China(GONG Shujuan);
    School of Medicine, Nankai University, Tianjin 300071, China(ZHENG Li);
    Department of Cardiology, the Sixth Medical Centre, Chinese PLA General Hospital, Beijing 100041, China(YANG Zeng’ao, LIU Yuqi)
  • Received:2025-01-16 Online:2025-08-20 Published:2025-08-19
  • Contact: LIU Yuqi, Email:ametuofo980869@163.com

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摘要： 目的 探索全身炎症反应指数(SIRI)与老年高尿酸血症病人全因死亡和心血管病死亡之间的关系,并构建预测模型,以改善风险分层,指导临床决策。 方法 本研究为前瞻性队列研究,纳入来自NHANES(1999—2010)数据库的1997例老年高尿酸血症病人。采用单因素及多因素Cox回归分析探讨SIRI与全因死亡及心血管病死亡的关系并确定关键预测因素,构建预测模型并评估性能,利用X-tile软件确定最佳的风险分层截断值。 结果 随访(中位随访152个月)期间,共有1131例病人死亡,其中330例死于心血管疾病。升高的SIRI与全因死亡(HR=1.17,95%CI:1.13~1.22,P<0.001)和心血管病死亡(HR=1.44,95%CI:1.28~1.62,P<0.001)独立相关。基于SIRI构建的预测模型在全因死亡(AUC=0.722)和心血管病死亡(AUC=0.797)预测方面均表现出良好的区分度、准确性和临床实用性,风险分层后的群体存在显著差异(log-rank P<0.001)。 结论 SIRI是老年高尿酸血症病人全因死亡和心血管病死亡的独立预测因子。基于SIRI构建的预测模型具有较好的区分度、准确性及临床决策价值,能够为临床个性化风险评估和决策提供科学依据。

关键词: 全身炎症反应指数, 老年人, 高尿酸血症, 全因死亡, 心血管病死亡

Abstract: Objective To explore the relationship between systemic inflammatory response index (SIRI) and all-cause death as well as cardiovascular mortality in the elderly patients with hyperuricemia, and to develop an effective mortality risk prediction model based on SIRI to improve risk stratification and guide clinical personalized decision-making. Methods This was a prospective cohort study that included 1997 elderly patients with hyperuricemia from the NHANES (1999—2010) database. Univariate and multivariate Cox regression analysis was used to explore the relationship between SIRI and all-cause death as well as cardiovascular mortality, and identify the key predictive factors. A corresponding risk prediction model was constructed. The model’s performance was evaluated by internal validation and area under the curve (AUC). Additionally, X-tile software was used to determine the optimal cutoff for risk stratification. Results During a median follow-up of 152 months, 1131 participants died, of which 330 died from cardiovascular diseases. Elevated SIRI was independently associated with both all-cause mortality (HR=1.17, 95% CI: 1.13－1.22, P<0.001) and cardiovascular mortality (HR=1.44, 95% CI: 1.28－1.62, P<0.001). The prediction model based on SIRI showed good performance in predicting all-cause mortality (AUC=0.722) and cardiovascular mortality (AUC=0.797). Calibration curves and clinical decision curve analysis further validated the accuracy and clinical applicability of the model. Risk stratification analysis showed significant differences between the stratified groups (log-rank P<0.001). Conclusions SIRI is an independent predictor of all-cause mortality and cardiovascular mortality in the elderly patients with hyperuricemia. The predictive model based on SIRI demonstrates good discriminative ability, accuracy, and clinical decision-making value, which can aid in personalized risk assessment and guide clinical decision-making.

Key words: systemic inflammatory response index, aged, hyperuricemia, all-cause mortality, cardiovascular mortality

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