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Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data.

TitleEstimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data.
Publication TypeJournal Article
Year of Publication2015
AuthorsMatsushita K, Coresh JJ, Sang Y, Chalmers J, Fox C, Guallar E, Jafar T, Jassal SK, Landman GWD, Muntner P, Roderick P, Sairenchi T, Schöttker B, Shankar A, Shlipak M, Tonelli M, Townend J, van Zuilen A, Yamagishi K, Yamashita K, Gansevoort R, Sarnak M, Warnock DG, Woodward M
Secondary Authorsrnlöv JÄ
Corporate AuthorsCKD Prognosis Consortium
JournalLancet Diabetes Endocrinol
Volume3
Issue7
Pagination514-25
Date Published2015 Jul
ISSN2213-8595
KeywordsAdult, Albuminuria, Cardiovascular Diseases, Coronary Disease, Creatinine, Female, Follow-Up Studies, Glomerular Filtration Rate, Heart Failure, Humans, Male, Middle Aged, Risk Factors, Stroke
Abstract

BACKGROUND: The usefulness of estimated glomerular filtration rate (eGFR) and albuminuria for prediction of cardiovascular outcomes is controversial. We aimed to assess the addition of creatinine-based eGFR and albuminuria to traditional risk factors for prediction of cardiovascular risk with a meta-analytic approach.

METHODS: We meta-analysed individual-level data for 637 315 individuals without a history of cardiovascular disease from 24 cohorts (median follow-up 4·2-19·0 years) included in the Chronic Kidney Disease Prognosis Consortium. We assessed C statistic difference and reclassification improvement for cardiovascular mortality and fatal and non-fatal cases of coronary heart disease, stroke, and heart failure in a 5 year timeframe, contrasting prediction models for traditional risk factors with and without creatinine-based eGFR, albuminuria (either albumin-to-creatinine ratio [ACR] or semi-quantitative dipstick proteinuria), or both.

FINDINGS: The addition of eGFR and ACR significantly improved the discrimination of cardiovascular outcomes beyond traditional risk factors in general populations, but the improvement was greater with ACR than with eGFR, and more evident for cardiovascular mortality (C statistic difference 0·0139 [95% CI 0·0105-0·0174] for ACR and 0·0065 [0·0042-0·0088] for eGFR) and heart failure (0·0196 [0·0108-0·0284] and 0·0109 [0·0059-0·0159]) than for coronary disease (0·0048 [0·0029-0·0067] and 0·0036 [0·0019-0·0054]) and stroke (0·0105 [0·0058-0·0151] and 0·0036 [0·0004-0·0069]). Dipstick proteinuria showed smaller improvement than ACR. The discrimination improvement with eGFR or ACR was especially evident in individuals with diabetes or hypertension, but remained significant with ACR for cardiovascular mortality and heart failure in those without either of these disorders. In individuals with chronic kidney disease, the combination of eGFR and ACR for risk discrimination outperformed most single traditional predictors; the C statistic for cardiovascular mortality fell by 0·0227 (0·0158-0·0296) after omission of eGFR and ACR compared with less than 0·007 for any single modifiable traditional predictor.

INTERPRETATION: Creatinine-based eGFR and albuminuria should be taken into account for cardiovascular prediction, especially when these measures are already assessed for clinical purpose or if cardiovascular mortality and heart failure are outcomes of interest. ACR could have particularly broad implications for cardiovascular prediction. In populations with chronic kidney disease, the simultaneous assessment of eGFR and ACR could facilitate improved classification of cardiovascular risk, supporting current guidelines for chronic kidney disease. Our results lend some support to also incorporating eGFR and ACR into assessments of cardiovascular risk in the general population.

FUNDING: US National Kidney Foundation, National Institute of Diabetes and Digestive and Kidney Diseases.

DOI10.1016/S2213-8587(15)00040-6
Alternate JournalLancet Diabetes Endocrinol
PubMed ID26028594
PubMed Central IDPMC4594193
Grant ListHHSN268201100012C / HL / NHLBI NIH HHS / United States
K23 DK067303 / DK / NIDDK NIH HHS / United States
U01 DK035073 / DK / NIDDK NIH HHS / United States
HHSN268201100010C / HL / NHLBI NIH HHS / United States
UL1 RR025005 / RR / NCRR NIH HHS / United States
HHSN268201100008C / HL / NHLBI NIH HHS / United States
UL1 TR001079 / TR / NCATS NIH HHS / United States
K23 DK002904 / DK / NIDDK NIH HHS / United States
U10 EY006594 / EY / NEI NIH HHS / United States
HHSN268201100007C / HL / NHLBI NIH HHS / United States
HHSN268201100011C / HL / NHLBI NIH HHS / United States
P30 DK079626 / DK / NIDDK NIH HHS / United States
R01 AG007181 / AG / NIA NIH HHS / United States
R01 DK073217 / DK / NIDDK NIH HHS / United States
HHSN268201100006C / HL / NHLBI NIH HHS / United States
R01 DK031801 / DK / NIDDK NIH HHS / United States
U01 NS041588 / NS / NINDS NIH HHS / United States
N01 HC095169 / HC / NHLBI NIH HHS / United States
R01 HL080477 / HL / NHLBI NIH HHS / United States
HHSN268201100009C / HL / NHLBI NIH HHS / United States
HHSN268201100005C / HL / NHLBI NIH HHS / United States
R01 DK100446 / DK / NIDDK NIH HHS / United States
R01 AG028507 / AG / NIA NIH HHS / United States
N01 HC095159 / HC / NHLBI NIH HHS / United States