Evidence mapPaperPMID 39071115Full record

ReviewTherapeutic advances in endocrinology and metabolism2024

Chronic kidney disease combined with metabolic syndrome is a non-negligible risk factor.

Lirong Lin, Xianfeng Pan, Yuanjun Feng, Jurong Yang

Abstract readReview
In one paragraph

Review in Therapeutic advances in endocrinology and metabolism, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Effects ofMolecules (Basel, Switzerland) · 2026
    Article
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  3. Review
  4. Review
  5. Article
  6. Article
  7. Observational
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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

4 authors.

Lirong LinDepartment of Nephrology, The Third Affiliated Hospital of Chongqing Medical University (General Hospital), Chongqing, China.
Xianfeng PanDepartment of Nephrology, Chongqing Kaizhou District People's Hospital of Chongqing, Chongqing, China.
Yuanjun FengDepartment of Nephrology, Guizhou Aerospace Hospital, Guizhou 563000, China.
Jurong YangDepartment of Nephrology, The Third Affiliated Hospital of Chongqing Medical University (General Hospital), Chongqing 401120, China.ORCID https://orcid.org/0000-0002-6792-4617

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic syndrome (MetS) is a group of conditions characterized by hypertension (HTN), hyperglycaemia or insulin resistance (IR), hyperlipidaemia, and abdominal obesity. MetS is associated with a high incidence of cardiovascular events and mortality and is an independent risk factor for chronic kidney disease (CKD). MetS can cause CKD or accelerate the progression of kidney disease. Recent studies have found that MetS and kidney disease have a cause-and-effect relationship. Patients with CKD, those undergoing kidney transplantation, or kidney donors have a significantly higher risk of developing MetS than normal people. The present study reviewed the possible mechanisms of MetS in patients with CKD, including the disorders of glucose and fat metabolism after kidney injury, IR, HTN and the administration of glucocorticoid and calcineurin inhibitors. In addition, this study reviewed the effect of MetS in patients with CKD on important target organs such as the kidney, heart, brain and blood vessels, and the treatment and prevention of CKD combined with MetS. The study aims to provide strategies for the diagnosis, treatment and prevention of CKD in patients with MetS.

Indexed as

chronic kidney diseaseglucose metabolic disordersmetabolic syndromepathological characteristicstherapeutics

Identifiers

PMID39071115
PMCPMC11273817

What Socratic holds

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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 Socratic graph.