Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts
Open accessAbstract
Both low eGFR and albuminuria are known risk factors for ESRD. This paper focuses on their joint contribution to ESRD and other kidney outcomes. We performed a collaborative meta-analysis of 9 general population cohorts with 845,125 participants and 8 cohorts with 173,892 participants selected because of high risk for chronic kidney disease. Both eGFR and albuminuria were tested as risk factors for ESRD, acute kidney injury and progressive chronic kidney disease. In general population cohorts, the risk for ESRD was unrelated to eGFR at values 75–105 ml/min/1.73m2 and increased exponentially at lower eGFR. Hazard ratios (95% confidence interval) at eGFR 60, 45, and 15 (versus 95) ml/min/1.73m2 were 3.69 (2.36–5.76), 29.3 (19.5–44.1) and 454.9 (112.4–1840.2), respectively, after adjustment for albumin-to-creatinine ratio and cardiovascular risk factors. Albuminuria was associated with ESRD risk linearly without thresholds. Adjusted hazard ratios at albumin-to-creatinine ratios 30, 300 and 1000 (versus 5) mg/g were 4.87 (2.30–10.3), 13.4 (5.49–32.7) and 28.4 (14.9–54.2), respectively. eGFR and albuminuria were multiplicatively associated with ESRD, without evidence for interaction. Similar, but numerically less pronounced associations were observed for acute kidney injury and progressive chronic kidney disease. The findings in high risk cohorts were generally comparable to those in general population cohorts. In conclusion, lower eGFR and higher albuminuria are risk factors for ESRD, acute kidney injury and progressive chronic kidney disease independent of each other and of cardiovascular risk factors, both in the general population and high risk cohorts.
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The absolute benefits of SGLT2 inhibition are likely to be at least as large for people with eGFR lower than 45 as for those with higher eGFRs.
“the absolute benefits of SGLT2 inhibition are likely to be at least as large as those for people with higher eGFRs.30”
From SGLT2 inhibitors for the prevention of kidney failure in patients with type 2 diabetes: a systematic review and meta-analysis (2019) · cites this paper as [30]
The Discussion reports substantially higher risk of end-stage renal disease at lower eGFR, supporting the claim’s premise that people with lower eGFR have more kidney risk. The paper does not study SGLT2 inhibition or compare its absolute benefits across eGFR groups, so it cannot establish the treatment-benefit comparison. (LLM, conf=0.84)
Experimental — accuracy not yet measuredIndividuals with eGFR lower than 45 are at much greater risk of kidney failure than those with higher eGFRs.
“Because these individuals are at much greater risk of kidney failure than those with higher eGFRs”
From SGLT2 inhibitors for the prevention of kidney failure in patients with type 2 diabetes: a systematic review and meta-analysis (2019) · cites this paper as [30]
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- Authors
- Gansevoort, R. T., Matsushita, K., van der Velde, M., Astor, B. C., Woodward, M., Levey, A. S., de Jong, P. E., & Coresh, J.
- Affiliations
- University Medical Center Groningen (NL)
- Johns Hopkins University (US)
- The University of Sydney (AU)
- Tufts Medical Center (US)
- Corresponding author
- Gansevoort, Ron T.
- ORCID
- Venue
- Kidney International
- Publisher
- Elsevier BV
- Published
- 2011-07
- Volume
- 80
- Issue
- 1
- Pages
- 93-104
- ISSN
- 0085-2538 (ISSN-L)
- PMC
- PMC3959732
- OpenAlex
- W2048196288
- Semantic Scholar
- b03cd681e8bfb7230f62b95a96ec16783f08fa14
- Cited by
- 883
- References
- 54
- Citations by year
- 2026: 22 · 2025: 49 · 2024: 76 · 2023: 69 · 2022: 62 · 2021: 47 · 2020: 60 · 2019: 53 · 2018: 42 · 2017: 58 · 2016: 63 · 2015: 65 · 2014: 59 · 2013: 65 · 2012: 66
- FWCI
- 9.18
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Kidney International (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Funders
- Johns Hopkins University
- Nierstichting
- National Institutes of Health (n01hc045133-001, n01hc085079-024, n01hc015103-009, n01hc095169-003, n01hc085086-022, n01hc25195-41-0-1, n01hc55222-0-0-0, n01hc95159-40-0-1, n01hc075150-004, n01hc035129-010)
- National Institute on Aging (R01AG020098, R01AG007181, R01AG023629, R01AG028507, R01AG015928, R01AG027058)
- National Heart, Lung, and Blood Institute (HHSN268201 100012C, N01 HC085086, HHSN268201100007C, N01-HC095169, HHSN2682 01100008C, HH-SN-268201100006C, HHSN268201100011C, N01 HC085079, HHSN268201100005C, R01HL068140, N01 HC035129, HHSN268201100010C, N01-HC-095159, N01 HC015103, N01-HC-025195, HHSN268201200036C, HHSN26820 1100009C, N01 HC055222, R01HL043232, R01HL080295, N01 HC075150, N01 HC045133)
- National Eye Institute (U10EY006594)
- National Institute of Diabetes and Digestive and Kidney Diseases (K23DK067303, R01DK031801, K23DK002904, R01DK073217, U01DK035073)
- National Institute of Neurological Disorders and Stroke (U01NS041588)
- Topics
- Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
- Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
- Health Sciences › Medicine › Nephrology › Dialysis and Renal Disease Management
- Keywords
- estimated glomerular filtration rate, albuminuria, albumin-creatinine ratio, end-stage renal disease, acute kidney injury, chronic kidney disease progression, renal outcomes, cardiovascular risk factors, multiplicative interaction, risk factors
- MeSH terms
- Aged, Albuminuria, Creatinine, Female, Glomerular Filtration Rate, Humans, Kidney Failure, Chronic, Male, Middle Aged, Prognosis, Risk Factors, Cohort Studies, Proportional Hazards Models
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 ›
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