Evidence map›Paper›PMID 38322631›Full record

ArticleKidney diseases (Basel, Switzerland)2024

Thickened Perirenal Fat Predicts Poor Renal Outcome in Patients with Immunoglobulin A Nephropathy: A Population-Based Retrospective Cohort Study.

Hongtu Hu, Zongwei Zhang, Zikang Liu, Fan Chu, Jialu Ran, Wei Liang

Abstract read
In one paragraph

Article in Kidney diseases (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Obesity-Related Glomerulosclerosis-How Adiposity Damages the Kidneys.International journal of molecular sciences · 2025
    Review
  2. Obesity-related glomerulopathy: How it happens and future perspectives.Diabetic medicine : a journal of the British Diabetic Association · 2025
    Review
  3. 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

6 authors.

Hongtu HuDivision of Nephrology, Renmin Hospital of Wuhan University, Wuhan, China.
Zongwei ZhangDivision of Nephrology, Renmin Hospital of Wuhan University, Wuhan, China.
Zikang LiuDivision of Nephrology, Renmin Hospital of Wuhan University, Wuhan, China.
Fan ChuDivision of Nephrology, Renmin Hospital of Wuhan University, Wuhan, China.
Jialu RanDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Wei LiangDivision of Nephrology, Renmin Hospital of Wuhan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Perirenal fat is a pad that fills the retroperitoneal space outside the kidney, which affects kidney function in various ways. However, the association between perirenal fat and IgA nephropathy (IgAN) has not yet been elucidated. This study aimed to investigate the role of perirenal fat in predicting IgAN progression. Methods: A total of 473 patients with biopsy-proven IgAN and follow-up information were recruited, and perirenal fat thickness (PFT) was measured using color Doppler ultrasonography at renal biopsy. Patients were divided into two groups according to the median PFT: the low-PFT group (PFT ≤1.34 cm, Results: Compared to healthy subjects, patients with IgAN showed significantly higher PFT. After a median follow-up of 50 months, 75 of 473 patients (15.9%) with IgAN reached renal composite endpoints. Among those, 13 of 239 patients (5.4%) were in the low PFT group, and 62 of 234 patients (26.5%) were in the high PFT group ( Conclusion: This study indicated a positive relationship between PFT at renal biopsy and renal progression in patients with IgAN, suggesting that perirenal fat might act as a marker of poor prognosis in patients with IgAN.

Indexed as

Immunoglobulin A nephropathyPerirenal fatRenal prognosis

Identifiers

PMID38322631
PMCPMC10843190

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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.