Pan JianJiang, Cai XiXuan, Chen JieRu, Xu MingYing, Hu JingYu, Mao YueChun, Chen Tao, Li LuSha, Jin MengQi, Chen LiYing
Department of General Practice, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310020, People's Republic of China.
Department of General Practice, Jianqiao Community Health Service Center, Hangzhou, Zhejiang, 310021, People's Republic of China.
J Inflamm Res. 2024 Nov 8;17:8501-8511. doi: 10.2147/JIR.S493111. eCollection 2024.
Understanding the role of systemic inflammation in the development of Metabolic Syndrome (MetS) is crucial for identifying individuals at a higher risk of this cluster of conditions that increase the risk of heart disease, stroke, and diabetes.
A retrospective cohort study was conducted with 4,312 participants who were free from MetS at the study's onset and had high-sensitivity C-reactive protein (hsCRP) levels measured. Latent class trajectory modeling was utilized to identify distinct hsCRP trajectory patterns. Multivariable regression and proportional hazards analyses were employed to evaluate the predictive value of hsCRP trajectories for the development of MetS.
During the 1.63-year follow-up period, 1,308 participants developed metabolic syndrome (MetS). Individuals with high hsCRP levels exhibited a significantly increased risk of developing MetS compared to those with low hsCRP levels (HR = 1.062, 95% CI 1.103-1.113). The hsCRP trajectory analysis identified three distinct groups: low-stable, increasing, and decreasing. The decreasing and increasing hsCRP trajectory groups demonstrated a 1.408-fold (95% CI 1.115-1.779) and a 1.618-fold (95% CI 1.288-2.033) increased risk of MetS, respectively.
This study suggests that participants with higher baseline hsCRP levels and increasing hsCRP trajectories are associated with a progression toward MetS. Long-term hsCRP trajectories may serve as useful tools for identifying individuals at higher risk of MetS who could benefit from targeted preventive and therapeutic interventions.
了解全身炎症在代谢综合征（MetS）发生发展中的作用，对于识别患这种增加心脏病、中风和糖尿病风险的疾病集群风险较高的个体至关重要。
对4312名参与者进行了一项回顾性队列研究，这些参与者在研究开始时无代谢综合征且测量了高敏C反应蛋白（hsCRP）水平。采用潜在类别轨迹模型来识别不同的hsCRP轨迹模式。使用多变量回归和比例风险分析来评估hsCRP轨迹对代谢综合征发生的预测价值。
在1.63年的随访期内，1308名参与者发生了代谢综合征（MetS）。与hsCRP水平低的个体相比，hsCRP水平高的个体发生MetS的风险显著增加（HR = 1.062，95% CI 1.103 - 1.113）。hsCRP轨迹分析确定了三个不同的组：低稳定组、上升组和下降组。hsCRP轨迹下降组和上升组发生MetS的风险分别增加了1.408倍（95% CI 1.115 - 1.779）和1.618倍（95% CI 1.288 - 2.033）。
本研究表明，基线hsCRP水平较高且hsCRP轨迹上升的参与者与向MetS的进展相关。长期的hsCRP轨迹可能是识别代谢综合征高风险个体的有用工具，这些个体可能从有针对性的预防和治疗干预中获益。
