Evidence map›Paper›PMID 34666784›Full record

ArticleNutrition & metabolism2021

Serum uric acid and risk of incident chronic kidney disease: a national cohort study and updated meta-analysis.

Nianwei Wu, Jing Xia, Sen Chen, Chuan Yu, Ying Xu, Chengfu Xu, Tong Yan, Ningxiu Li, Yanjun Liu, Xiong-Fei Pan

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nutrition & metabolism, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Review
  7. Review
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 3 countries.

Nianwei WuDepartment of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Jing XiaDepartment of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Sen ChenDepartment of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Chuan YuDepartment of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Ying XuKidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Chengfu XuDepartment of Gastroenterology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Tong YanCenter for Obesity and Metabolic Health, The Third People's Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China.
Ningxiu LiDepartment of Health and Social Behavior, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Yanjun LiuCenter for Obesity and Metabolic Health, The Third People's Hospital of Chengdu & The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China. liuyanjun_001@163.com.
Xiong-Fei PanDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA. pxiongfei@gmail.com.ORCID http://orcid.org/0000-0002-9350-9230
Sichuan University · CNThird People's Hospital of Chengdu · CNZhejiang University · CNThe George Institute for Global Health · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe prospectively examined the association between serum uric acid (SUA) levels and chronic kidney disease (CKD) in China and updated the evidence through a comprehensive meta-analysis of prospective studies worldwide.

methodsOur original analyses were based on data from the China Health and Retirement Longitudinal Study. The primary exposure of interest was SUA at baseline, and the main outcome was incident CKD. Logistic regression models were used to examine the association between SUA levels and incident CKD. A meta-analysis was performed to pool our effect estimate and those from other cohort studies.

resultsDuring a 4-year follow-up, 180 participants developed incident CKD. Participants in the highest SUA quartile were 2.73 times as likely to develop incident CKD compared to those in the lowest quartile (multivariable-adjusted OR, 2.73; 95% CI, 1.65-4.50). Each 1 mg/dL increment in the SUA levels was associated with a 49% increased risk of incident CKD (multivariable-adjusted OR, 1.49; 95% CI, 1.28-1.74). In the meta-analysis of 30 cohort studies (including the current study), pooled relative risks (95% CIs) of incident CKD were 1.15 (1.10-1.21) for SUA each 1 mg/dL increment, 1.22 (1.14-1.30) for the highest versus lowest SUA group, and 1.17 (1.12-1.23) for hyperuricemia versus no hyperuricemia.

conclusionsBaseline SUA levels were associated with higher risk of incident CKD in middle-aged and elderly Chinese adults, and this positive association was confirmed in the meta-analysis of multiple cohort studies. Our findings may imply that SUA levels need to be routinely monitored for future CKD risk.

Indexed as

ChineseChronic kidney diseaseCohort studyMeta-analysisSerum uric acid

Identifiers

PMID34666784
PMCPMC8524911
OpenAlexW3207194738

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.