中国全科医学 ›› 2026, Vol. 29 ›› Issue (28): 4179-4186.DOI: 10.12114/j.issn.1007-9572.2025.0497

• 论著·慢性病共病专题研究 • 上一篇    下一篇

心血管代谢性共病与估算肾小球滤过率的关联性研究

卢鸿润1,2, 张睿1,2, 赵钰1,2, 李佳禛1,2, 王为强1,*()   

  1. 1.234000 安徽省宿州市,安徽医科大学附属宿州医院(安徽省宿州市立医院)全科医学科
    2.230000 安徽省合肥市,安徽医科大学
  • 收稿日期:2025-12-15 修回日期:2026-06-17 出版日期:2026-10-05 发布日期:2026-09-02
  • 通讯作者: 王为强

  • 作者贡献:

    卢鸿润提出主要研究目标,负责研究的构思与设计,研究的实施,数据分析及撰写论文;张睿,赵钰进行数据的收集与整理,统计学处理,图、表的绘制与展示;李佳禛进行论文的修订;王为强负责试验研究规划及监督、论文质量审校及指导,对论文负责。

  • 基金资助:
    安徽省科技创新战略与软科学研究专项计划项目(202106f01050042)

Association of Cardiometabolic Comorbidity with Estimated Glomerular Filtration Rate

LU Hongrun1,2, ZHANG Rui1,2, ZHAO Yu1,2, LI Jiazhen1,2, WANG Weiqiang1,*()   

  1. 1. Department of General Medicine, Suzhou Hospital of Anhui Medical University (Suzhou Municipal Hospital of Anhui Province), Suzhou 234000, China
    2. Anhui Medical University, Hefei 230000, China
  • Received:2025-12-15 Revised:2026-06-17 Published:2026-10-05 Online:2026-09-02
  • Contact: WANG Weiqiang

摘要: 背景 心血管代谢性疾病(CMD)与慢性肾脏病(CKD)的发病风险和临床结局往往相互关联。估算肾小球滤过率(eGFR)作为评估肾脏功能的关键指标,有助于早期识别与干预CKD的发生。然而,现有研究多集中于单一CMD或其危险因素与CKD的关联,对于多种CMD并存这一普遍现象如何影响肾功能,尤其是不同共病数量与特定组合模式的差异化影响,尚缺乏深入探讨。 目的 探讨心血管代谢性共病(CMM)、不同CMD数量及组合模式与eGFR的关系,进而为CKD的早期识别和干预提供科学依据。 方法 数据源于安徽省心血管疾病高危人群早期筛查与综合干预项目,2017—2022年对安徽省宿州市等12个城市的社区常住居民进行调查,收集患者一般资料和生化指标,最终纳入5 707例35~75岁心血管疾病高危人群作为研究对象。根据CKD-EPI公式计算eGFR以评估肾功能,将eGFR≥90 mL·min-1·(1.73 m2)-1和<90 mL·min-1·(1.73 m2)-1的研究对象分为eGFR正常组(3 707例)和eGFR异常组(2 000例)。采用二元Logistic回归分析以评估CMM与eGFR的关系,并进一步探索CMD的累积数量和逐个累加数量及不同CMM组合对eGFR水平的影响。 结果 本研究人群中,CMM患病率高达51.3%。二元Logistic回归分析结果显示,在调整了年龄、性别、婚姻、高中以下学历、家庭年收入<5万元、农民、吸烟、饮酒、BMI和尿素氮(BUN)后,与非CMM人群相比,CMM患者eGFR异常的风险是非CMM患者的1.28倍(OR=1.280,95%CI=1.140~1.438,P<0.001);随着CMD数量增加,eGFR异常的风险分别为:2种(OR=1.428,95%CI=1.132~1.802,P=0.003),3种(OR=1.465,95%CI=1.126~1.905,P=0.004),4种(OR=2.352,95%CI=1.570~3.524,P<0.001);且CMD数量的增加与eGFR异常之间存在剂量-反应关系(OR=1.170,95%CI=1.098~1.247,P<0.001)。与非CMM(0~1种CMD)患者相比,患2种CMM患者的eGFR异常风险增加24%(OR=1.240,95%CI=1.091~1.409,P<0.001);当CMM数量增加到3种时,与患2种CMD患者对比差异性无统计学意义(OR=1.025,95%CI=0.855~1.230,P=0.789);4种及以上CMD相比3种CMD,eGFR异常风险增加60.5%(OR=1.605,95%CI=1.102~2.337,P=0.014)。在患有2种、3种及4种CMD的组合中,对eGFR影响最大组合分别是:高血压+心脏病(OR=2.245,95%CI=1.589~3.172,P<0.001)、高血压+糖尿病+心脏病(OR=2.269,95%CI=1.380~3.728,P=0.001)、高血压+糖尿病+血脂异常+脑卒中(OR=2.645,95%CI=1.997~3.713,P=0.021)。 结论 CMM及不同CMD数量、组合与eGFR异常风险密切相关。本研究提示,对CMD数量≥4种的个体进行重点筛查与综合管理,并阻断2~3种CMD向≥4种进展,同时关注特定的CMD组合模式可能是预防CKD、改善预后的有效策略。

关键词: 心血管疾病, 心血管代谢性共病, 心血管代谢性疾病, 肾小球滤过率, 慢性肾病, 安徽省

Abstract:

Background

Cardiometabolic diseases (CMDs) and chronic kidney disease (CKD) are closely interrelated in terms of disease risk and clinical outcomes. Estimated glomerular filtration rate (eGFR), a key indicator of renal function, is useful for the early identification and intervention of CKD. However, existing studies have mainly focused on the association between a single CMD, or its risk factors, and CKD. The impact of the coexistence of multiple CMDs, a common clinical phenomenon, on renal function remains insufficiently explored, particularly with regard to the differential effects of the number of comorbid conditions and specific disease combination patterns.

Objective

To investigate the associations of cardiometabolic multimorbidity (CMM), the number of CMDs, and specific CMD combination patterns with eGFR, thereby providing evidence for the early identification and intervention of CKD.

Methods

Data were obtained from the Early Screening and Comprehensive Intervention Program for High-risk Populations of Cardiovascular Disease in Anhui Province. From 2017 to 2022, community-dwelling residents from 12 cities in Anhui Province, including Suzhou, were surveyed. General demographic characteristics and biochemical indicators were collected. A total of 5 707 individuals aged 35-75 years at high risk of cardiovascular disease were ultimately included. eGFR was calculated using the CKD-EPI equation to assess renal function. Participants with eGFR≥90 mL·min-1·(1.73 m2)-1 and those with eGFR <90 mL·min-1·(1.73 m2)-1 were classified into the normal eGFR group (n=3 707) and abnormal eGFR group (n=2 000), respectively. Binary Logistic regression was used to evaluate the association between CMM and eGFR. The effects of the cumulative number of CMDs, stepwise increases in CMD number, and different CMM combination patterns on eGFR were further explored.

Results

The prevalence of CMM in the study population was 51.3%. Binary Logistic regression analysis showed that, after adjustment for age, sex, marital status, education below high school level, annual household income <50 000 RMB, farming occupation, smoking, alcohol consumption, body mass index, and blood urea nitrogen, patients with CMM had a 1.28-fold higher risk of abnormal eGFR than those without CMM (OR=1.280, 95%CI=1.140-1.438, P<0.001). With an increasing number of CMDs, the risks of abnormal eGFR were as follows: two CMDs, OR=1.428, 95%CI=1.132-1.802, P=0.003; three CMDs, OR=1.465, 95%CI=1.126-1.905, P=0.004; and four CMDs, OR=2.352, 95%CI=1.570-3.524, P<0.001. A dose-response relationship was observed between the increasing number of CMDs and abnormal eGFR (OR=1.170, 95%CI=1.098-1.247, P<0.001). Compared with individuals without CMM, defined as having 0-1 CMD, those with two CMDs had a 24% increased risk of abnormal eGFR (OR=1.240, 95%CI=1.091-1.409, P<0.001). When the number of CMDs increased to three, no statistically significant difference was observed compared with two CMDs (OR=1.025, 95%CI=0.855-1.230, P=0.789). Compared with individuals with three CMDs, those with four or more CMDs had a 60.5% increased risk of abnormal eGFR (OR=1.605, 95%CI=1.102-2.337, P=0.014). Among participants with two, three, and four CMDs, the combinations associated with the greatest impact on eGFR were hypertension plus heart disease (OR=2.245, 95%CI=1.589-3.172, P<0.001), hypertension plus diabetes plus heart disease (OR=2.269, 95%CI=1.380-3.728, P=0.001), and hypertension plus diabetes plus dyslipidemia plus stroke (OR=2.645, 95%CI=1.997-3.713, P=0.021), respectively.

Conclusion

CMM, as well as the number and combination patterns of CMDs, is closely associated with the risk of abnormal eGFR. These findings suggest that targeted screening and comprehensive management should be prioritized for individuals with four or more CMDs, while preventing the progression from two or three CMDs to four or more CMDs. In addition, attention to specific CMD combination patterns may represent an effective strategy for preventing CKD and improving prognosis.

Key words: Cardiovascular disease, Cardiometabolic comorbidity, Cardiometabolic diseases, Glomerular filtration rate, Chronic kidney disease, Anhui Province