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Article(id=1241034442983141679, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241034441380917539, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202406199, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1718208000000, receivedDateStr=2024-06-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773815268512, onlineDateStr=2026-03-18, pubDate=1749484800000, pubDateStr=2025-06-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773815268512, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773815268512, creator=13701087609, updateTime=1773815268512, updator=13701087609, issue=Issue{id=1241034441380917539, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='11', pageStart='1921', pageEnd='2112', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773815268130, creator=13701087609, updateTime=1773815340947, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241034746873049765, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241034441380917539, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241034746873049766, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241034441380917539, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1952, endPage=1956, ext={EN=ArticleExt(id=1241034443729727816, articleId=1241034442983141679, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association study of estimated glomerular filtration rate combined with albuminuria and coronary artery disease in the elderly population of China, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the association between overt proteinuria (OP) and moderately reduced estimated glomerular filtration rate (MG) in relation to the incidence of coronary artery disease (CAD).

Methods

The study targeted elderly individuals (aged ≥60 years) who completed at least two national basic public health service health examinations at a community health service center in Chengdu from 2017 to 2022. A total of 4 316 subjects were categorized into four groups based on the presence or absence of OP and MG: no OP no MG (NP[MG-]), OP no MG (OP[MG-]), no OP with MG (NP[MG+]),and OP with MG (OP[MG+]). An intrinsic time-dependent Cox analysis was conducted to evaluate the association of estimated glomerular filtration rate and proteinuria, individually or in combination, with the risk of CAD.

Results

The study included 4 316 subjects with a median follow-up time of 6.25 years, during which 419 developed new cases of CAD. The results indicated that compared to the group with both indicators negative, the risk of CAD increased by 15% (HR=1.15, 95% CI: 0.88-1.41) for those with moderately reduced estimated glomerular filtration rate (MG+), by 14% (HR=1.14, 95% CI: 0.76-1.51) for those with overt proteinuria (OP), and by 93% (HR=1.93, 95% CI: 1.50-2.37) for those with both indicators positive (OP[MG+]). The combined use of both indicators demonstrated a superior discriminatory effect on CAD risk compared to the use of either indicator alone.

Conclusion

Routine screening for estimated glomerular filtration rate and albuminuria in the elderly population is recommended, as the combined assessment of both indicators is more effective in identifying individuals at high risk for coronary artery disease.

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目的

探讨显性蛋白尿(overt proteinuria, OP)和中度降低估计肾小球滤过率(moderately reduced estimated glomerular filtration rate, MG)单独和联合使用与冠状动脉疾病(coronary artery disease, CAD)发病的关联。

方法

以2017 —2022年在成都市某社区卫生服务中心至少完成二次国家基本公共卫生服务健康体检的老年(年龄≥60岁)人群作为研究对象。根据有无OP和MG将4 316例受试者分为四组：无OP无MG (NP[MG-])、有OP无MG (OP[MG-])、无OP有MG (NP[MG+])和有OP有MG (OP[MG+])组。进行内在时间依存Cox分析以评价单独或联合使用估计肾小球滤过率、蛋白尿与CAD发生风险的关联。

结果

研究共纳入4 316名受试者。中位随访时间为6.25年，419名受试者新发CAD。研究结果显示相比两个指标均为阴性时，单独估计肾小球滤过率中度降低(MG+)、单独白蛋白尿显性(OP)及两个指标均为阳性(OP[MG+])时，CAD发病风险分别增加15% (HR=1.15，95%CI：0.88～1.41)、14% (HR=1.14，95%CI：0.76～1.51)、93% (HR=1.93，95%CI：1.50～2.37)。两个指标联合使用对CAD发生风险的区分效果优于单独使用某一指标。

结论

应对老年人群常规检测估计肾小球滤过率和白蛋白尿，两个指标联合评估相比单一指标更有助于识别CAD高风险人群。

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李雅馨，E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=TauYgSpyCkr9WoIAVvQ2lA==, magXml=1RAgTlLkZlSIM/cTFbsInQ==, pdfUrl=null, pdf=aFhoHIjvkXE9qV4R8eEy7Q==, pdfFileSize=796013, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=7CO7Ty8B/0jNRK6UXQLBjw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=DVUH18qQYIjXn265JoerHg==, mapNumber=null, authorCompany=null, fund=null, authors=

刘杨楠与韩昕玥为共同第一作者

杨楠（2002年—），女，硕士在读，研究方向：非传染病流行病学；

韩昕玥（2000年—），女，硕士在读，研究方向：流行病与卫生统计学；

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Renal Failure,2024, 46(1): 2327494., articleTitle=Predictive effect of estimated glomerular filtrate rate by creatinine or cystatin C on mortality in patients with coronary artery disease, refAbstract=null), Reference(id=1241050846658613916, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, doi=null, pmid=null, pmcid=null, year=2020, volume=48, issue=1, pageStart=10, pageEnd=46, url=null, language=null, rfNumber=[15], rfOrder=17, authorNames=国家卫生健康委员会疾病预防控制局, 国家心血管病中心, 中国医学科学院阜外医院, journalName=中华心血管病杂志, refType=null, unstructuredReference=国家卫生健康委员会疾病预防控制局，国家心血管病中心，中国医学科学院阜外医院，等.中国高血压健康管理规范（2019）[J].中华心血管病杂志，2020，48（1）：10-46., articleTitle=中国高血压健康管理规范（2019）, refAbstract=null), Reference(id=1241050846750888607, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, doi=null, pmid=null, pmcid=null, year=2020, volume=48, issue=1, pageStart=10, pageEnd=46, url=null, language=null, rfNumber=[15], rfOrder=18, authorNames=National Health Commission Disease Control and Prevention Bureau, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, journalName=Chinese Journal of Cardiology, refType=null, unstructuredReference=National Health Commission Disease Control and Prevention Bureau,National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, et al. 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Chinese Journal of Cardiology, 2020, 48(1): 10-46.(In Chinese), articleTitle=National guideline for hypertension management in China (2019), refAbstract=null)], funds=[Fund(id=1241050842934071892, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, awardId=24NSFC240028, language=CN, fundingSource=四川省自然科学基金重点项目(24NSFC240028), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241050827385787362, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, xref=1., ext=[AuthorCompanyExt(id=1241050827389981667, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, companyId=1241050827385787362, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Epidemiology and Health Statistics, Wesat China School of Public Health, Sichuan University / West China Fourth Hospital, Chengdu, 610041, China), AuthorCompanyExt(id=1241050827398370277, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, companyId=1241050827385787362, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.四川大学华西公共卫生学院/华西第四医院 流行病与卫生统计学系，四川 成都 610041)]), AuthorCompany(id=1241050827528393706, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, xref=2., ext=[AuthorCompanyExt(id=1241050827545170925, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, companyId=1241050827528393706, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.四川大学华西公共卫生学院/华西第四医院 中毒/肾脏内科，四川 成都 610041)])], figs=[ArticleFig(id=1241050841264738839, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, language=EN, label=Figure 1, caption=Kaplan-Meier survival plots for renal function index, figureFileSmall=6GO50mAM+33Vozm99iDk7A==, figureFileBig=xSezXxf6AfvwCTYlH4f/ow==, tableContent=null), ArticleFig(id=1241050841600283167, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, language=CN, label=图1, caption=肾功能相关指标的Kaplan-Meier生存曲线图

注：图A、B、C分别为eGFR-蛋白尿联合分组、eGFR、蛋白尿各分组的生存曲线图。

, figureFileSmall=6GO50mAM+33Vozm99iDk7A==, figureFileBig=xSezXxf6AfvwCTYlH4f/ow==, tableContent=null), ArticleFig(id=1241050841818386985, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, language=EN, label=Figure 2, caption=Forest plot of hypertension subgroup analysis of renal function indices and CAD, figureFileSmall=uAChO7laJ3R7XQs54Ba7Zw==, figureFileBig=pUVdEAvu5aj144Q6KdQyxQ==, tableContent=null), ArticleFig(id=1241050842078433843, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, language=CN, label=图2, caption=肾功能指标与CAD的高血压亚组分析森林图, figureFileSmall=uAChO7laJ3R7XQs54Ba7Zw==, figureFileBig=pUVdEAvu5aj144Q6KdQyxQ==, tableContent=null), ArticleFig(id=1241050842200068665, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, language=EN, label=Table 1, caption=

Comparison of general data of general population with CAD group and non-CAD group ［n（%），M（P25，P75）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名称总人数非CAD组CAD组χ2/W值P值
基础指标
性别1.655 b0.198
男性1 258 (29.15)1 124 (28.84)134 (31.98)
女性3 058 (70.85)2 773 (71.16)285 (68.02)
教育水平1.933 b0.380
小学及以下3 696 (85.63)3 328 (85.40)368 (87.83)
初中或高中475 (11.01)437 (11.21)38 (9.07)
大专及以上145 (3.36)132 (3.39)13 (3.10)
婚姻状况12.086 b<0.050
已婚3 456 (80.07)3 148 (80.78)308 (73.51)
未婚/离婚/丧偶860 (19.93)749 (19.22)111 (26.49)
吸烟24.041 b<0.050
从不吸烟2 432 (56.35)2 149 (55.14)283 (67.54)
已戒烟927 (21.48)856 (21.97)71 (16.95)
吸烟957 (22.17)892 (22.89)65 (15.51)
年龄（岁）74 (70, 80)74 (70, 79)78 (74, 83)547 743.500 a<0.050
BMI（kg/m2）24.07 (22.18, 26.14)24.04 (22.15, 26.08)24.28 (22.41, 26.61)766 050.500 a<0.050
肾功能相关指标
eGFR12.960 b<0.050
MG-3 654 (84.66)3 325 (85.32)329 (78.52)
MG+662 (15.34)572 (14.68)90 (21.48)
蛋白尿2.360 b0.124
OP3 944 (91.38)3 570 (91.61)374 (89.26)
NP372 (8.62)327 (8.39)45 (10.74)
eGFR-蛋白尿15.119 b<0.050
NP[MG-]3 382 (78.36)3 083 (79.11)299 (71.36)
NP[MG+]562 (13.02)487 (12.50)75 (17.90)
OP[MG-]272 (6.30)242 (6.21)30 (7.16)
OP[MG+]100 (2.32)85 (2.18)15 (3.58)
SBP（mm Hg）139 (128, 153)139 (128, 153)139 (129, 153)806 065.000 a0.669
TC（mmol/L）5.06 (4.39, 5.71)5.07 (4.43, 5.72)4.94 (4.12, 5.63)891 018.000 a<0.050
TG（mmol/L）1.3 (0.96, 1.85)1.3 (0.96, 1.85)1.36 (0.99, 1.86)791 752.000 a<0.050
LDL-C（mmol/L）2.79 (2.28, 3.28)2.79 (2.28, 3.28)2.77 (2.2, 3.24)842 254.000 a0.286
HDL-C（mmol/L）1.43 (1.22, 1.69)1.43 (1.22, 1.7)1.38 (1.2, 1.61)895 887.000 a<0.050
FBG（mmol/L）5.23 (4.77, 5.89)5.23 (4.77, 5.88)5.24 (4.77, 5.94)810 853.500 a0.818
), ArticleFig(id=1241050842351063615, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, language=CN, label=表1, caption=

总人群中CAD组与非CAD组的一般资料比较［n（%），M（P25，P75）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名称总人数非CAD组CAD组χ2/W值P值
基础指标
性别1.655 b0.198
男性1 258 (29.15)1 124 (28.84)134 (31.98)
女性3 058 (70.85)2 773 (71.16)285 (68.02)
教育水平1.933 b0.380
小学及以下3 696 (85.63)3 328 (85.40)368 (87.83)
初中或高中475 (11.01)437 (11.21)38 (9.07)
大专及以上145 (3.36)132 (3.39)13 (3.10)
婚姻状况12.086 b<0.050
已婚3 456 (80.07)3 148 (80.78)308 (73.51)
未婚/离婚/丧偶860 (19.93)749 (19.22)111 (26.49)
吸烟24.041 b<0.050
从不吸烟2 432 (56.35)2 149 (55.14)283 (67.54)
已戒烟927 (21.48)856 (21.97)71 (16.95)
吸烟957 (22.17)892 (22.89)65 (15.51)
年龄（岁）74 (70, 80)74 (70, 79)78 (74, 83)547 743.500 a<0.050
BMI（kg/m2）24.07 (22.18, 26.14)24.04 (22.15, 26.08)24.28 (22.41, 26.61)766 050.500 a<0.050
肾功能相关指标
eGFR12.960 b<0.050
MG-3 654 (84.66)3 325 (85.32)329 (78.52)
MG+662 (15.34)572 (14.68)90 (21.48)
蛋白尿2.360 b0.124
OP3 944 (91.38)3 570 (91.61)374 (89.26)
NP372 (8.62)327 (8.39)45 (10.74)
eGFR-蛋白尿15.119 b<0.050
NP[MG-]3 382 (78.36)3 083 (79.11)299 (71.36)
NP[MG+]562 (13.02)487 (12.50)75 (17.90)
OP[MG-]272 (6.30)242 (6.21)30 (7.16)
OP[MG+]100 (2.32)85 (2.18)15 (3.58)
SBP（mm Hg）139 (128, 153)139 (128, 153)139 (129, 153)806 065.000 a0.669
TC（mmol/L）5.06 (4.39, 5.71)5.07 (4.43, 5.72)4.94 (4.12, 5.63)891 018.000 a<0.050
TG（mmol/L）1.3 (0.96, 1.85)1.3 (0.96, 1.85)1.36 (0.99, 1.86)791 752.000 a<0.050
LDL-C（mmol/L）2.79 (2.28, 3.28)2.79 (2.28, 3.28)2.77 (2.2, 3.24)842 254.000 a0.286
HDL-C（mmol/L）1.43 (1.22, 1.69)1.43 (1.22, 1.7)1.38 (1.2, 1.61)895 887.000 a<0.050
FBG（mmol/L）5.23 (4.77, 5.89)5.23 (4.77, 5.88)5.24 (4.77, 5.94)810 853.500 a0.818
), ArticleFig(id=1241050842548195907, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, language=EN, label=Table 2, caption=

Survival analysis of renal function index and CAD

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名原始模型模型Ⅰ模型Ⅱ
HR值(95%CI)P值HR值(95%CI)P值HR值(95%CI)P值
eGFR
MG-——————
MG+1.40 (1.17～1.63)<0.051.31 (1.08～1.55)<0.051.23 (0.99～1.47)0.092
蛋白尿
NP——————
OP1.42 (1.14～1.71)<0.051.31 (1.03～1.6)0.0611.31 (1.02～1.6)0.069
eGFR-蛋白尿
NP[MG-]——————
NP[MG+]1.28 (1.02～1.54)0.0601.21 (0.94～1.47)0.1601.15 (0.88～1.41)0.313
OP[MG-]1.20 (0.84～1.57)0.3211.12 (0.76～1.49)0.5391.14 (0.76～1.51)0.498
OP[MG+]2.21 (1.78～2.64)<0.051.94 (1.51～2.37)<0.051.93 (1.50～2.37)<0.05
), ArticleFig(id=1241050842674025030, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241034442983141679, language=CN, label=表2, caption=

肾功能指标与CAD的生存分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名原始模型模型Ⅰ模型Ⅱ
HR值(95%CI)P值HR值(95%CI)P值HR值(95%CI)P值
eGFR
MG-——————
MG+1.40 (1.17～1.63)<0.051.31 (1.08～1.55)<0.051.23 (0.99～1.47)0.092
蛋白尿
NP——————
OP1.42 (1.14～1.71)<0.051.31 (1.03～1.6)0.0611.31 (1.02～1.6)0.069
eGFR-蛋白尿
NP[MG-]——————
NP[MG+]1.28 (1.02～1.54)0.0601.21 (0.94～1.47)0.1601.15 (0.88～1.41)0.313
OP[MG-]1.20 (0.84～1.57)0.3211.12 (0.76～1.49)0.5391.14 (0.76～1.51)0.498
OP[MG+]2.21 (1.78～2.64)<0.051.94 (1.51～2.37)<0.051.93 (1.50～2.37)<0.05
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估计肾小球滤过率联合白蛋白尿与中国老年人群冠心病的关联研究
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杨楠 1 , 韩昕玥 1 , 的机卓玛 1 , 胡梦婕 1 , 陈馨 1 , 姜侠 1 , 龙璐 1 , 廖加强 1 , 樊萌语 1 , 汪川 1 , 吕良 1 , 马天佩 1 , 张韬 1 , 李佳圆 1 , 李雅馨 2 , 华西健康老龄与重大慢性病医防融合研究课题组 1
现代预防医学 | 流行病与统计方法 2025,52(11): 1952-1956
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现代预防医学 | 流行病与统计方法 2025, 52(11): 1952-1956
估计肾小球滤过率联合白蛋白尿与中国老年人群冠心病的关联研究
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杨楠1, 韩昕玥1, 的机卓玛1, 胡梦婕1, 陈馨1, 姜侠1, 龙璐1, 廖加强1, 樊萌语1, 汪川1, 吕良1, 马天佩1, 张韬1, 李佳圆1, 李雅馨2 , 华西健康老龄与重大慢性病医防融合研究课题组1
作者信息
  • 1.四川大学华西公共卫生学院/华西第四医院 流行病与卫生统计学系，四川 成都 610041
  • 2.四川大学华西公共卫生学院/华西第四医院 中毒/肾脏内科，四川 成都 610041

    • 杨楠（2002年—），女，硕士在读，研究方向：非传染病流行病学；

    韩昕玥（2000年—），女，硕士在读，研究方向：流行病与卫生统计学；

通讯作者:

李雅馨，E-mail:
Association study of estimated glomerular filtration rate combined with albuminuria and coronary artery disease in the elderly population of China
Nan YANG1, Xin-yue HAN1, ’JI Zhuo-ma DI1, Meng-jie HU1, Xin CHEN1, Xia JIANG1, Lu LONG1, Jia-qiang LIAO1, Meng-yu FAN1, Chuan WANG1, Liang LV1, Tian-pei MA1, Tao ZHANG1, Jia-yuan LI1, Ya-xin LI2 , Research Group on Health Aging and Integration of Major Chronic Disease Prevention, West China Hospital of Sichuan University1
Affiliations
  • Department of Epidemiology and Health Statistics, Wesat China School of Public Health, Sichuan University / West China Fourth Hospital, Chengdu, 610041, China
出版时间: 2025-06-10 doi: 10.20043/j.cnki.MPM.202406199
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摘要
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目的

探讨显性蛋白尿(overt proteinuria, OP)和中度降低估计肾小球滤过率(moderately reduced estimated glomerular filtration rate, MG)单独和联合使用与冠状动脉疾病(coronary artery disease, CAD)发病的关联。

方法

以2017 —2022年在成都市某社区卫生服务中心至少完成二次国家基本公共卫生服务健康体检的老年(年龄≥60岁)人群作为研究对象。根据有无OP和MG将4 316例受试者分为四组：无OP无MG (NP[MG-])、有OP无MG (OP[MG-])、无OP有MG (NP[MG+])和有OP有MG (OP[MG+])组。进行内在时间依存Cox分析以评价单独或联合使用估计肾小球滤过率、蛋白尿与CAD发生风险的关联。

结果

研究共纳入4 316名受试者。中位随访时间为6.25年，419名受试者新发CAD。研究结果显示相比两个指标均为阴性时，单独估计肾小球滤过率中度降低(MG+)、单独白蛋白尿显性(OP)及两个指标均为阳性(OP[MG+])时，CAD发病风险分别增加15% (HR=1.15，95%CI：0.88～1.41)、14% (HR=1.14，95%CI：0.76～1.51)、93% (HR=1.93，95%CI：1.50～2.37)。两个指标联合使用对CAD发生风险的区分效果优于单独使用某一指标。

结论

应对老年人群常规检测估计肾小球滤过率和白蛋白尿，两个指标联合评估相比单一指标更有助于识别CAD高风险人群。

估计肾小球滤过率  /  白蛋白尿  /  冠心病
Objective

To explore the association between overt proteinuria (OP) and moderately reduced estimated glomerular filtration rate (MG) in relation to the incidence of coronary artery disease (CAD).

Methods

The study targeted elderly individuals (aged ≥60 years) who completed at least two national basic public health service health examinations at a community health service center in Chengdu from 2017 to 2022. A total of 4 316 subjects were categorized into four groups based on the presence or absence of OP and MG: no OP no MG (NP[MG-]), OP no MG (OP[MG-]), no OP with MG (NP[MG+]),and OP with MG (OP[MG+]). An intrinsic time-dependent Cox analysis was conducted to evaluate the association of estimated glomerular filtration rate and proteinuria, individually or in combination, with the risk of CAD.

Results

The study included 4 316 subjects with a median follow-up time of 6.25 years, during which 419 developed new cases of CAD. The results indicated that compared to the group with both indicators negative, the risk of CAD increased by 15% (HR=1.15, 95% CI: 0.88-1.41) for those with moderately reduced estimated glomerular filtration rate (MG+), by 14% (HR=1.14, 95% CI: 0.76-1.51) for those with overt proteinuria (OP), and by 93% (HR=1.93, 95% CI: 1.50-2.37) for those with both indicators positive (OP[MG+]). The combined use of both indicators demonstrated a superior discriminatory effect on CAD risk compared to the use of either indicator alone.

Conclusion

Routine screening for estimated glomerular filtration rate and albuminuria in the elderly population is recommended, as the combined assessment of both indicators is more effective in identifying individuals at high risk for coronary artery disease.

Estimated glomerular filtration rate  /  Albuminuria  /  Coronary artery disease
杨楠, 韩昕玥, 的机卓玛, 胡梦婕, 陈馨, 姜侠, 龙璐, 廖加强, 樊萌语, 汪川, 吕良, 马天佩, 张韬, 李佳圆, 李雅馨, 华西健康老龄与重大慢性病医防融合研究课题组. 估计肾小球滤过率联合白蛋白尿与中国老年人群冠心病的关联研究. 现代预防医学, 2025 , 52 (11) : 1952 -1956 . DOI: 10.20043/j.cnki.MPM.202406199
Nan YANG, Xin-yue HAN, ’JI Zhuo-ma DI, Meng-jie HU, Xin CHEN, Xia JIANG, Lu LONG, Jia-qiang LIAO, Meng-yu FAN, Chuan WANG, Liang LV, Tian-pei MA, Tao ZHANG, Jia-yuan LI, Ya-xin LI, Research Group on Health Aging and Integration of Major Chronic Disease Prevention, West China Hospital of Sichuan University. Association study of estimated glomerular filtration rate combined with albuminuria and coronary artery disease in the elderly population of China[J]. Modern Preventive Medicine, 2025 , 52 (11) : 1952 -1956 . DOI: 10.20043/j.cnki.MPM.202406199
正文
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冠状动脉疾病（coronary artery disease, CAD）又称为冠心病，是一群包含稳定型心绞痛、非稳定型心绞痛、心肌梗塞和猝死的疾病。中国60岁以上人群冠心病的患病率为27.8‰，病死率为全年龄段病死率的第一位。且老年人群冠心病患者的住院费用相较其他年龄组偏高，给我国带来巨大的疾病经济负担[1]。高血压是CAD最重要的危险因素之一，高血压患者发生CAD的风险是正常人群的4倍[2]。危险因素防控是心血管病一级预防的核心，因此，对老年人群，尤其是老年高血压人群的CAD发生风险进行早期评估对于促进疾病预防至关重要。
慢性肾脏病（chronic kidney disease, CKD）是各种原因引起的慢性肾脏结构和功能障碍（肾脏损害病史大于3个月），表现为肾小球滤过率（estimated glomerular filtration rate, eGFR）降低和（或）尿白蛋白肌酐比升高[3]。CAD是CKD最重要的并发症之一。事实上，高达50%的CKD患者在达到需要肾脏替代治疗的终末期肾病之前就死于CAD[4]。通过广泛的流行病学研究确定，eGFR和白蛋白尿作为CKD的主要诊断指标，也可改善CAD风险预测，甚至超越了传统的CAD危险因素。白蛋白尿和eGFR是CAD事件发生的独立危险因素，eGFR下降和尿白蛋白增加与CAD发病率增加均密切相关[5-6]。然而，通常只单独研究eGFR或尿白蛋白对CAD发生风险的影响，如目前《中国心血管病一级预防指南》对于心血管病风险的评估中只考虑了CKD疾病分期对心血管病发生风险的影响，将处在CKD3/4期者列为心血管病高危人群，而CKD疾病分期仅与eGFR值有关，与白蛋白尿无关[7]。很少有研究调查eGFR联合白蛋白尿与CAD发病风险的相关性。所以本研究旨在评估老年人群中eGFR联合白蛋白尿与CAD发生风险之间的关联。
1　对象与方法
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1.1　研究对象
本研究基于社区体检的基本公共卫生服务的纵向数据。该基本公共卫生服务自2017年起在成都市郫都区红光社区卫生服务中心服务区域收集老年人群2017—2022年参与基本公共卫生老年体检项目及指标，与四川省卫生健康委信息中心病案首页疾病诊断信息关联，形成2017年起的老年自然人群数据库。本研究人群基于该基本公共卫生服务，研究对象纳入标准：（1）年龄大于等于60岁；（2）至少参与2次健康体检；（3）有尿白蛋白试纸检测结果；（4）eGFR在30.0～90.0 ml/(min·1.73m2)。排除标准：（1）基线时已患CAD者；（2）患有恶心肿瘤、感染性疾病者；（3）问卷调查信息及体格、生化检查指标等资料不完善者。最终共纳入研究对象4 316人。本研究并通过四川大学华西第四医院/华西公共卫生学院伦理委员会批准（Gwll2024175），所有信息收集均获得了参与者的知情同意。。
1.2　数据收集
所有受试者均接受了问卷调查，收集性别、年龄、文化程度、婚姻状况、吸烟史、服药史、既往疾病史等基本数据；使用标准方法进行体格检查，收集老年人身高、体重、血压（SBP）等数据；收集老年人的血检数据，包括血清肌酐（Scr）、总胆固醇（TC）、甘油三酯（TG）、高密度脂蛋白胆固醇（HDL-C）、低密度脂蛋白胆固醇（LDL-C）、空腹血糖（FBG）和尿白蛋白等生化指标。
根据血清肌酐水平、年龄和性别来估算eGFR，利用慢性肾脏病流行病学协作公式（the Chronic Kidney Disease Epidemiology Collaboration equation, CKD-EPI公式）计算。CKD-EPI公式[8]：（1）女性：①Scr≤0.7 mg/dl, eGFR=144×［Scr（mg/dl）/0.7］-0.329×（0.993）年龄；②Scr>0.7 mg/dl, eGFR=144×［Scr（mg/dl）/0.7］-1.209×（0.993）年龄。（2）男性：①Scr≤0.9 mg/dl, eGFR=141×［Scr（mg/dl）/0.9］-0.411×（0.993）年龄；②Scr>0.9 mg/dl, eGFR=141×［Scr（mg/dl）/0.9］-1.209×（0.993）年龄。Scr单位换算：1 mg/dl=88.4 μmol/L
中度降低的eGFR（moderately reduced estimated glomerular filtration rate, MG）定义为基线eGFR在30.0～60.0 ml/（min·1.73m2）。尿白蛋白通过试纸评估，将试纸的反应区浸入新鲜的中段尿液中，等待60 s左右待颜色反应稳定后，将试纸与颜色对照表进行比较，读取尿液中白蛋白的浓度。结果分为四个等级，基线结果为≥1+表明显性蛋白尿（overt proteinuria, OP）。
受试者被分为四组：无OP（NP）无MG（NP[MG-]）、有OP无MG（OP[MG-]）、NP有MG（NP[MG+]）和有OP有MG（OP[MG+]）。
1.3　分类和定义
新发CAD诊断定义为在随访期间受试者住院病案首页诊断记录为CAD（ICD10编码：I20-I25，包括I20心绞痛、I21急性心肌梗塞、I22并发性心肌梗塞、I23急性心肌梗塞的某些即期并发症、I24其它急性缺血性心脏病、I25慢性缺血性心脏病）。
高血压诊断定义为基线时受试者住院病案首页明确诊断为高血压者［ICD10编码：I10-15，包括I10特发性（原发性）高血压、I11高血压心脏病、I12高血压肾脏病、I13高血压心脏和肾脏病、I15继发性高血压］。
1.4　统计学方法
根据随访结束时是否发生CAD，对基线一般指标进行分组。符合正态分布的计量资料以（）表示，组间比较采用两独立样本t检验；不符合正态分布的计量资料以［M（P25，P75）］表示，组间比较采用Wilcoxon秩和检验；计数资料以相对数表示，组间比较采用χ2检验。采用Kaplan-Meier法、log-rank检验及Bonferroni方法估计、比较并矫正单独使用eGFR、蛋白尿和使用联合指标时的累积生存时间。由于在随访期间测得eGFR为随时间变化，采用内在时间依存Cox分析分析暴露与结局之间关联，单独eGFR、蛋白尿和联合指标以分类变量分别纳入模型，使用方差膨胀因子VIF来检测混杂因素间的共线性。进一步，根据根据基线血压控制情况（血压控制在正常范围和血压异常）进行亚组分析。使用R语言软件4.2.3进行数据分析，双侧检验水准α=0.05。
2　结果
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2.1　基本情况
共计4 316例样本被纳入研究，共计有9 686条eGFR记录。纳入研究的样本中男性有1 258例（29.15%），年龄范围为60～98岁。在平均（6.82±1.21）年的随访中有419位（9.71%）参与者新诊断为CAD。与未发生CAD的参与者相比，发生CAD的患者的婚姻状况、吸烟、年龄、BMI、eGFR、eGFR联合蛋白尿、TC、TG、HDL-C组间差异具有统计学意义（P<0.05），参与者基线一般状况见表1。
2.2　肾功能指标与CAD发病风险的关联
本研究的中位随访时间为6.25年，有9.71%（419/4 316）的参与者发生了CAD事件，采用Kaplan-Meier法估计各肾功能指标的累积生存时间，具体结果见图1。eGFR-蛋白尿和eGFR各组间累积生存时间差异有统计学意义（P<0.05），蛋白尿各组间累积生存时间差异无统计学意义（P>0.05）。
Cox模型拟合结果如表2，在不调整任何因素的情况下，与MG-组相比，MG+组的参与者发生CAD的风险为1.40倍，与NP组相比，OP组发生CAD的风险为1.42倍，与NP[MG-]组相比，OP[MG+]组发生CAD的风险为2.21倍。在调整了性别、年龄、教育水平和婚姻状况后（模型I）后，蛋白尿对CAD发病的影响未能观察到统计上显著的差异，与MG-组相比，MG+组的参与者发生CAD的风险为1.31倍，与NP[MG-]组相比，OP[MG+]组发生CAD的风险为1.94倍。进而调整了吸烟史、LSBP、BMI、TC、TG、FBG、HDL-C、LDL-C（模型II）后，eGFR和蛋白尿对CAD发病的影响未能观察到显著的统计学差异，与NP[MG-]组相比，OP[MG+]组发生CAD的风险为1.93倍。
使用方差膨胀因子VIF评估模型Ⅱ中自变量的共线性。结果显示变量间不存在存在显著的共线性（VIF<10），不影响模型的参数估计。
2.3　肾功能指标与CAD发病风险的亚组分析
根据高血压将人群分为非高血压组和高血压组。亚组分析结果见图2，结果显示在非高血压人群中，与全阴性的组相比，单独使用eGFR和蛋白尿时发生CAD的风险差异无统计学意义。与NP[MG-]组相比，OP[MG-]组发生CAD的风险为1.87倍。在高血压人群中，与全阴性的组相比，单独使用eGFR和蛋白尿时发生CAD的风险差异无统计学意义。与NP[MG-]组相比，OP[MG+]组发生CAD的风险为1.69倍。
3　讨论
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本研究评估了两个主要的肾脏疾病诊断指标eGFR和白蛋白尿在4 316名老年人中与CAD发生风险的关联。在老年人群中，与两个指标均为阴性的组相比，单独eGFR中度降低的组以及单独尿白蛋白阳性的组，其发病风险的差异均无统计学意义；而两个指标均为阳性时，老年人群发生CAD的风险增加1.93倍。
eGFR和白蛋白尿通常被视为CAD结局的独立决定因素[5-6]。事实上，2012年肾脏疾病改善全球结局（Kidney Disease Improving Global Outcomes，KDIGO）指南图表显示白蛋白尿和eGFR类别在2个轴上，提示这两个危险因素之间存在正交或独立关系[9]。大多数流行病学分析尚未对这种作用进行检验。2017年有一项在中国地区开展的研究得到的结果与本研究结果相一致，该研究结果提示在肾功能相对保留（eGFR中度降低）的患者中，控制尿白蛋白对于心血管风疾病发生风险和死亡率方面的预后具有更大的意义和积极影响，结合eGFR和尿白蛋白肌酐比可以更准确地预测心血管疾病的发生风险[10]。但该研究是在糖尿病人群中开展，而本研究聚焦于老年人群以及老年高血压人群，提供了不同人群中的证据。
eGFR与尿白蛋白和CAD之间关联的确切机制尚不完全清楚，但来自动物和人类研究的证据表明，尿白蛋白与内皮糖萼和其他内皮结构异常有关，这可能导致炎症和内皮功能障碍[11-12]。尿白蛋白通过诱导内皮细胞的炎症反应和氧化应激，损伤内皮功能，而内皮细胞在血管健康中起着至关重要的作用，调节血管的收缩和舒张、炎症反应以及血栓形成。降低的eGFR对心血管系统有许多影响，包括抑制红细胞生成和血小板功能，血脂异常、高血压和血管钙化[13]。降低的eGFR与颈动脉斑块总面积和左心室肥厚有关，表明肾功能与冠状动脉钙化以及动脉粥样硬化之间存在潜在联系[14]。尿白蛋白水平升高和eGFR水平下降通过以上生物学机制影响心血管系统，从而增加心血管疾病的风险。然而，需要进一步的机制研究来阐明eGFR和尿白蛋白水平与心血管疾病发生风险较高之间关联的确切机制。
亚组分析结果表明，在老年高血压人群中，两个指标联合可能更适合作为评估CAD风险的有效指标。高血压是肾功能损害的常见病因，导致eGFR下降和尿白蛋白升高。《中国高血压健康管理规范2019》中关于综合评估心血管疾病总体风险这一条例中，对于高血压患者发生心脑血管疾病的主要危险因素纳入了血脂、尿酸等生化指标，但没有推荐对高血压患者进行常规的eGFR和尿白蛋白检测[15]。
综上所述，本研究基于60岁以上的老年人群，发现在评估CAD风险方面，联合使用eGFR和尿白蛋白相较于单独使用eGFR和尿白蛋白具有更好的优势。根据我们的研究结果，应该意识到eGFR水平降低和尿白蛋白水平升高的潜在临床影响。我们建议在老年人群，尤其是老年高血压患者中常规检测eGFR和尿白蛋白，来帮助评估心血管风险。本研究还存在一定的局限性。首先，本研究的数据来源于基本公共卫生数据库，缺乏在研究开始时明确选择研究对象和在随访过程中定向收集数据的能力，收集的纵向数据可能因研究对象的流失而导致样本的代表性不好。且作为一项观察性研究，因果关系的推断受限。其次，尿白蛋白是通过试纸定性测定，而没有通过定量测定方法获得具体的尿白蛋白浓度和总量。试纸定性分析虽然具有较高的灵敏度，但其检测下限相对较高，可能无法识别低浓度的尿白蛋白。使用定量分析方法能够精确测量尿白蛋白的浓度，即使在低浓度下也能提供可靠的结果，从而提高分析结果的准确性和可靠性。最后，使用的统计学方法内在时间依存Cox虽然充分利用了重复测量的数据，但是没有考虑个体内部的随机效应。
基金
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  • 四川省自然科学基金重点项目(24NSFC240028)
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2025年第52卷第11期
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doi: 10.20043/j.cnki.MPM.202406199
  • 接收时间：2024-06-13
  • 首发时间：2026-03-18
  • 出版时间：2025-06-10
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  • 收稿日期：2024-06-13
基金
四川省自然科学基金重点项目(24NSFC240028)
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    1.四川大学华西公共卫生学院/华西第四医院 流行病与卫生统计学系，四川 成都 610041
    2.四川大学华西公共卫生学院/华西第四医院 中毒/肾脏内科，四川 成都 610041

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2种不同金属材料的力学参数
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species		 占总种数比例
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total species (%)		 属
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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