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胰岛素抵抗代谢评分对中国关节炎患者心血管疾病的预测价值:一项前瞻性队列研究。

Predictive value of insulin resistance metabolic score for cardiovascular disease in Chinese arthritis patients: a prospective cohort study.

作者信息

Ke Wen-Kai, Xu Ling-Ling, Luo Ni

机构信息

Department of Gerontology, CR & WISCO General Hospital, Wuhan University of Science and Technology, Wuhan, Hubei, China.

Wuhan University of Science and Technology, Wuhan, Hubei, China.

出版信息

Rheumatology (Oxford). 2025 Jun 1;64(6):3388-3395. doi: 10.1093/rheumatology/keaf048.

Abstract

OBJECTIVES

Although patients with arthritis have significantly increased cardiovascular disease (CVD) risk, effective prediction tools remain limited. This study aimed to evaluate the predictive value of the Metabolic Score for Insulin Resistance (METS-IR) for CVD events among Chinese patients with arthritis.

METHODS

Using data from the China Health and Retirement Longitudinal Study (CHARLS), we conducted a 7-year prospective cohort study (2011-2018) involving 1059 patients with arthritis. The primary exposure was baseline METS-IR, and the primary outcome was incident CVD. Multivariate Cox regression models were used to analyse the association between METS-IR and CVD risk, adjusting for demographic characteristics and lifestyle factors.

RESULTS

After adjusting for confounding factors, each quartile increase in METS-IR was associated with a 36% increased risk of CVD (hazard ratio [HR] = 1.36, 95% CI: 1.14-1.61, P < 0.001). Compared with the lowest quartile, the highest quartile showed a 63% increased risk (HR = 1.63, 95% CI: 1.12-2.37, P < 0.05), demonstrating a significant dose-response relationship (P for trend < 0.05).

CONCLUSION

METS-IR serves as an effective tool for predicting CVD risk among Chinese patients with arthritis, providing new strategies for early risk identification and prevention.

摘要

目的

尽管关节炎患者的心血管疾病(CVD)风险显著增加,但有效的预测工具仍然有限。本研究旨在评估胰岛素抵抗代谢评分(METS-IR)对中国关节炎患者发生CVD事件的预测价值。

方法

利用中国健康与养老追踪调查(CHARLS)的数据,我们进行了一项为期7年的前瞻性队列研究(2011 - 2018年),纳入1059例关节炎患者。主要暴露因素为基线METS-IR,主要结局为新发CVD。采用多变量Cox回归模型分析METS-IR与CVD风险之间的关联,并对人口统计学特征和生活方式因素进行校正。

结果

在对混杂因素进行校正后,METS-IR每增加一个四分位数,CVD风险增加36%(风险比[HR]=1.36,95%可信区间:1.14 - 1.61,P<0.001)。与最低四分位数相比,最高四分位数的风险增加了63%(HR=1.63,95%可信区间:1.12 - 2.37,P<0.05),显示出显著的剂量反应关系(趋势P<0.05)。

结论

METS-IR可作为预测中国关节炎患者CVD风险的有效工具,为早期风险识别和预防提供了新策略。

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