Evidence map›Paper›PMID 34585311›Full record

SynthesisInternational urology and nephrology2022

Circulating irisin level in chronic kidney disease patients: a systematic review and meta-analysis.

Wenyuan Gan, Wenli Chen, Tianyu Li, Danni Shao, Fang Xu, Shanshan Huo, Chenchen Li, Zhenhua Yang, Xingruo Zeng

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in International urology and nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

11 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Association between serum irisin levels and blood pressure in patients undergoing hemodialysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2024
    Article
  7. Chronic kidney disease combined with metabolic syndrome is a non-negligible risk factor.Therapeutic advances in endocrinology and metabolism · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. 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

9 authors at 2 institutions in 1 country.

Wenyuan GanDepartment of Nephrology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China.
Wenli ChenDepartment of Nephrology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China.
Tianyu LiDepartment of Nephrology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China.
Danni ShaoDepartment of Nephrology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China.
Fang XuDepartment of Nephrology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China.
Shanshan HuoDepartment of Nephrology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China.
Chenchen LiDepartment of Nephrology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China.
Zhenhua YangDepartment of Nephrology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China.
Xingruo ZengDepartment of Nephrology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China. zengxingruo@163.com.
Huazhong University of Science and Technology · CNCentral Hospital of Wuhan · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIrisin is not only a myokine but also an adipokine that is critical in many diseases including in the development of such diseases as obesity, diabetes mellitus, metabolic syndrome, coronary artery disease, and chronic inflammation. However, the association between irisin and chronic kidney disease (CKD) is unclear. This systematic review aimed to assess circulating irisin levels in patients with CKD and compare them with those in non-CKD patients.

methodsPubMed, EMBASE, CENTRAL, ISI Web of Science, and CNKI were searched to identify observational studies of circulating irisin levels in patients with CKD. Two reviewers independently searched the databases and screened studies according to the inclusion criteria. Data were extracted using a standardized collection form. Meta-analysis was performed to compare the differences in circulating irisin levels between CKD and non-CKD patients.

resultsA total of 9 studies (6 cross-sectional and 3 case controls) involving 859 CKD patients and 393 non-CKD individuals were selected. The pooled data indicated that circulating irisin concentrations were significantly lower in CKD nondialysis patients (WMD = - 84.79, 95% CI - 170.23, 0.50; p < 0.05), peritoneal dialysis patients (WMD = - 235.81, 95% CI - 421.99, - 49.62; p = 0.01), and hemodialysis patients (WMD = - 217.46, 95% CI - 381.35, - 53.57; p = 0.009) than in healthy controls.

conclusionsThis study confirmed that irisin levels were decreased in patients with CKD. Moreover, circulating irisin levels were lower in dialysis patients than in nondialysis patients.

Indexed as

Diabetes MellitusMetabolic SyndromeRenal Insufficiency, ChronicCross-Sectional StudiesFemaleFibronectinsHumansMaleFibronectinsChronic kidney diseaseDialysisIrisinMeta-analysis

Identifiers

PMID34585311
OpenAlexW3203411179

What OpenQuestion holds

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Registered trials

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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.