Xu Xuehong, Ma Rulin, Zhang Xianghui, Guo Heng, Keerman Mulatibieke, Wang Xinping, Li Yu, Maimaitijiang Remina, He Jia, Guo Shuxia
Department of Public Health, Shihezi University School of Medicine, Shihezi, China.
Department of National Health Commission Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases, The First Affiliated Hospital of Shihezi University Medical College, Shihezi, China.
Ann Med. 2024 Dec;56(1):2427907. doi: 10.1080/07853890.2024.2427907. Epub 2024 Dec 1.
It is unclear whether changing trajectories of renal function will increase the risk prediction information of cardiovascular disease (CVD). This study aimed to evaluate the trajectory patterns of estimated glomerular filtration rate (eGFR) and the association between eGFR trajectories and CVD risk.
A total of 4742 participants were included in the cohort from the 51st Regiment of Xinjiang Production and Construction Corps. The study endpoint was the occurrence of CVD events. eGFR trajectories were identified using a linear mixed-effects model in four distinct patterns. Multivariate Cox proportional hazards models analysed the correlations between eGFR trajectories and CVD.
During a median follow-up period of 5.7 years, a total of 559 (11.8%) CVD, 404 (8.5%) myocardial infarction (MI), 244 (5.2%) ischemic stroke (IS), and 62 (1.3%) heart failure (HF) incidents occurred. After multivariable adjustment, gradual decline trajectory increased the risk of CVD ( 1.42, 95% 1.16-1.74), MI ( 1.41, 95% 1.11-1.79), and IS ( 1.41, 95% 1.04-1.92); gradual increase trajectory reduced the risk of CVD ( 0.40, 95% 0.25-0.64) and MI ( 0.49, 95% 0.29-0.81). Consistent results were obtained in sensitivity and subgroup analyses.
Decline and increase of renal function were related to the risk of CVD, MI, and IS in the rural areas of Xinjiang. Monitoring eGFR changing trajectory is of great significance in improving the risk of CVD.
肾功能轨迹的变化是否会增加心血管疾病(CVD)的风险预测信息尚不清楚。本研究旨在评估估计肾小球滤过率(eGFR)的轨迹模式以及eGFR轨迹与CVD风险之间的关联。
新疆生产建设兵团第51团的队列中总共纳入了4742名参与者。研究终点是CVD事件的发生。使用线性混合效应模型以四种不同模式确定eGFR轨迹。多变量Cox比例风险模型分析了eGFR轨迹与CVD之间的相关性。
在中位随访期5.7年期间,共发生559例(11.8%)CVD、404例(8.5%)心肌梗死(MI)、244例(5.2%)缺血性中风(IS)和62例(1.3%)心力衰竭(HF)事件。多变量调整后,逐渐下降轨迹增加了CVD(风险比[HR]=1.42,95%置信区间[CI]=1.16-1.74)、MI(HR=1.41,95%CI=1.11-1.79)和IS(HR=1.41,95%CI=1.04-1.92)的风险;逐渐上升轨迹降低了CVD(HR=0.40,95%CI=0.25-0.64)和MI(HR=0.49,95%CI=0.29-0.81)的风险。敏感性分析和亚组分析获得了一致的结果。
新疆农村地区肾功能的下降和上升与CVD、MI和IS的风险相关。监测eGFR变化轨迹对改善CVD风险具有重要意义。