Evidence map›Paper›PMID 37317534›Full record

ArticleRenal failure2023

Asprosin is positively associated with metabolic syndrome in hemodialysis patients: a cross-sectional study.

Jiandong Zhou, Weijie Yuan, Yunshan Guo, Yongfang Wang, Yuyang Dai, Ying Shen, Xuan Liu

Abstract read
In one paragraph

Article in Renal failure, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. 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

7 authors.

Jiandong ZhouDepartment of Nephrology, Shanghai General Hospital of Nanjing Medical University, Shanghai, China.
Weijie YuanDepartment of Nephrology, Shanghai General Hospital of Nanjing Medical University, Shanghai, China.
Yunshan GuoDepartment of Nephrology, Shanghai General Hospital of Nanjing Medical University, Shanghai, China.
Yongfang WangDepartment of Oncology Key Laboratory, Wujin Hospital Affiliated with Jiangsu University, Changzhou, China.
Yuyang DaiDepartment of Oncology Key Laboratory, Wujin Hospital Affiliated with Jiangsu University, Changzhou, China.
Ying ShenDepartment of Oncology Key Laboratory, Wujin Hospital Affiliated with Jiangsu University, Changzhou, China.
Xuan LiuDepartment of Nephrology, Shanghai General Hospital of Nanjing Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMetabolic syndrome (MS) has a high prevalence in hemodialysis patients. High asprosin levels are associated with the accumulation of adiposity and an increase in body weight, which may drive the development of this syndrome. The relationship between asprosin and MS in patients on hemodialysis has not been investigated. MATERIALS AND

methodsWe enrolled hemodialysis patients at the hemodialysis center of one hospital in May 2021. MS was defined by the International Diabetes Federation. Fasting serum asprosin levels were measured. ROC curve, multivariate logistic regression and Spearman's rank correlation analyses were performed.

resultsIn total, 134 patients were included, with 51 with MS and 83 without MS. Among the patients with MS, there was a significantly higher proportion of women (54.9%), prevalence of DM (

conclusionsFasting serum asprosin is positively correlated with MS and could be an independent risk factor for MS in hemodialysis patients.

Indexed as

Metabolic SyndromeCholesterol, LDLCross-Sectional StudiesFemaleHumansObesityRenal DialysisCholesterol, LDLAsprosinhemodialysismetabolic syndrome

Identifiers

PMID37317534
PMCPMC10274553

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.