Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 903

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

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

Open access
Matsushita, Kunihiro, Coresh, Josef, Sang, Yingying, Chalmers, John, Fox, Caroline, Guallar, Eliseo, Jafar, Tazeen, Jassal, Simerjot K, Landman, Gijs W D, Muntner, Paul, Roderick, Paul, Sairenchi, Toshimi, Schöttker, Ben, Shankar, Anoop, Shlipak, Michael, Tonelli, Marcello, Townend, Jonathan, van Zuilen, Arjan, Yamagishi, Kazumasa, Yamashita, Kentaro, Gansevoort, Ron, Sarnak, Mark, Warnock, David G, Woodward, Mark, Ärnlöv, Johan·2015·The Lancet Diabetes & Endocrinology

Abstract

Background The utility of estimated glomerular filtration rate (eGFR) and albuminuria for cardiovascular prediction is controversial. Methods We meta-analyzed individual-level data from 24 cohorts (with a median follow-up time longer than 4 years, varying from 4.2 to 19.0 years) in the Chronic Kidney Disease Prognosis Consortium (637,315 participants without a history of cardiovascular disease) and 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 5-year timeframe, contrasting prediction models consisting of traditional risk factors with and without creatinine-based eGFR and/or albuminuria (either albumin-to-creatinine ratio [ACR] or semi-quantitative dipstick proteinuria). 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] and 0.0065 [0.0042–0.0088], respectively) 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 demonstrated smaller improvement than ACR. The discrimination improvement with kidney measures 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 conditions. In participants with chronic kidney disease (CKD), the combination of eGFR and ACR for risk discrimination outperformed most single traditional predictors; the c-statistic for cardiovascular mortality declined by 0.023 [0.016–0.030] vs. <0.007 when omitting eGFR and ACR vs. any single modifiable traditional predictors, respectively. Interpretation Creatinine-based eGFR and albuminuria should be taken into account for cardiovascular prediction, especially when they are already assessed for clinical purpose and/or cardiovascular mortality and heart failure are the outcomes of interest (e.g., the European guidelines on cardiovascular prevention). ACR may have particularly broad implications for cardiovascular prediction. In CKD populations, the simultaneous assessment of eGFR and ACR will facilitate improved cardiovascular risk classification, supporting current CKD guidelines. Funding US National Kidney Foundation and NIDDK

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/s2213-8587(15)00040-6

Cites

10 of 10 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 10 references

Cited by

See all 903

Metadata

Authors
Matsushita, K., Coresh, J., Sang, Y., Chalmers, J., Fox, C., Guallar, E., Jafar, T., Jassal, S. K., Landman, G. W. D., 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, D. G., Woodward, M., & Ärnlöv, J.
Venue
The Lancet Diabetes & Endocrinology
Publisher
Elsevier BV
Published
2015-07
Volume
3
Issue
7
Pages
514-525
ISSN
2213-8587 (ISSN-L)
OpenAlex
W2161569030
Cited by
903
References
10
FWCI
10.25
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data. https://app.cochat.ai/papers/10.1016/s2213-8587(15)00040-6
The paper
Matsushita, K., Coresh, J., Sang, Y., Chalmers, J., Fox, C., Guallar, E., Jafar, T., Jassal, S. K., Landman, G. W. D., Muntner, P., Roderick, P., Sairenchi, T., Schöttker, B., Shankar, A., Shlipak, M., Tonelli, M., Townend, J., van Zuilen, A., Yamagishi, K., . . . Ärnlöv, J. (2015). Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data. The Lancet Diabetes & Endocrinology. https://doi.org/10.1016/s2213-8587(15)00040-6

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.