| Title: | Cystatin C-based estimated glomerular filtration rate and risk of stroke in the general population: a prospective cohort study |
| Journal: | Clinical Kidney Journal |
| Published: | 9 Aug 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37915909/ |
| DOI: | https://doi.org/10.1093/ckj/sfad188 |
| URL: | https://academic.oup.com/ckj/advance-article-pdf/doi/10.1093/ckj/sfad188/51078712/sfad188.pdf |
| Citations: | 1 (1 in last 2 years) as of 8 Aug 2024 |
Publication 10174
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Abstract
Background: Previous results on the association between the estimated glomerular filtration rate (eGFR) and stroke are mixed. Most studies derived the eGFR from serum creatinine, which is affected by non-kidney determinants and thus has possibly biased the association with stroke risk.</p>
Methods: In this cohort study, we included 429 566 UK Biobank participants (94.5% white, 54% women, age 56 ± 8 years) free of stroke at enrollment. The eGFRcys and eGFRcr were calculated with serum cystatin C and creatinine, respectively. Outcomes of interest were risk of total stroke and subtypes. We investigated the linear and nonlinear associations using Cox proportional hazards models and restricted cubic splines, corrected for regression dilution bias.</p>
Results: During an average follow-up of 10.11 years, 4427 incident strokes occurred, among which 3447 were ischemic and 1163 were hemorrhagic. After adjustment for confounders, the regression dilution-corrected hazard ratios (95% confidence intervals) for every 10 mL/min/1.73 m2 decrement in eGFRcys were 1.10 (1.05-1.14) for total stroke and 1.11 (1.08-1.15) for ischemic stroke. A similar pattern was observed with eGFRcr, although the association was weaker. When either type of eGFR was below 75 mL/min/1.73 m2, the risks of total and ischemic stroke increased exponentially as eGFR decreased. A U-shaped relationship was witnessed if eGFRcr was used instead. There was a null association between eGFR and hemorrhagic stroke.</p>
Conclusions: The risks of total stroke and ischemic stroke increased exponentially when the eGFRcys fell below 75 mL/min/1.73 m2.</p>
18 Authors
- Jinlan Liao
- Fei Xiao
- Liuqiao Yang
- Yanling Wei
- Congying Song
- Jing Li
- Sike Yu
- Yueqi Lu
- Jingwen Zhang
- Liang Dai
- Wei Liang
- Tao Li
- Zuying Xiong
- Yangfeng Wu
- Meg J Jardine
- Juan Jesus Carrero
- Ying Shan
- Xiaoyan Huang
1 Application
| Application ID | Title |
|---|---|
| 65814 | Leveraging functional genomics resources to improve the power of phenotype prediction -- a new machine learning approach |
Enabling scientific discoveries that improve human health