Evidence map›Paper›PMID 38983811›Full record

ReviewWorld journal of diabetes2024

Clinical characteristics and treatment compounds of obesity-related kidney injury.

Tuo-Hua Mao, Han-Qi Huang, Chuan-Hai Zhang

Abstract readReview
In one paragraph

Review in World journal of diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Tuo-Hua MaoDepartment of Endocrinology, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China.
Han-Qi HuangDepartment of Endocrinology, Hubei No. 3 People's Hospital of Jianghan University, Wuhan 430033, Hubei Province, China.
Chuan-Hai ZhangDepartment of Physiology, UT Southwestern Medical Center, Dallas, TX 75390, United States. chuanhai.zhang@utsouthwestern.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disorders in energy homeostasis can lead to various metabolic diseases, particularly obesity. The obesity epidemic has led to an increased incidence of obesity-related nephropathy (ORN), a distinct entity characterized by proteinuria, glomerulomegaly, progressive glomerulosclerosis, and renal function decline. Obesity and its associated renal damage are common in clinical practice, and their incidence is increasing and attracting great attention. There is a great need to identify safe and effective therapeutic modalities, and therapeutics using chemical compounds and natural products are receiving increasing attention. However, the summary is lacking about the specific effects and mechanisms of action of compounds in the treatment of ORN. In this review, we summarize the important clinical features and compound treatment strategies for obesity and obesity-induced kidney injury. We also summarize the pathologic and clinical features of ORN as well as its pathogenesis and potential therapeutics targeting renal inflammation, oxidative stress, insulin resistance, fibrosis, kidney lipid accumulation, and dysregulated autophagy. In addition, detailed information on natural and synthetic compounds used for the treatment of obesity-related kidney disease is summarized. The synthesis of detailed information aims to contribute to a deeper understanding of the clinical treatment modalities for obesity-related kidney diseases, fostering the anticipation of novel insights in this domain.

Indexed as

Clinical features and treatmentCompoundsKidney injuryObesityObesity-related nephropathy

Identifiers

PMID38983811
PMCPMC11229974

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.