Evidence mapPaperPMID 39713133Full record

SynthesisPeerJ2024

Non-obese non-alcoholic fatty liver disease and the risk of chronic kidney disease: a systematic review and meta-analysis.

Yixian You, Xiong Pei, Wei Jiang, Qingmin Zeng, Lang Bai, Taoyou Zhou, Xiaoju Lv, Hong Tang, Dongbo Wu

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in PeerJ, 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. Review
  2. Article
  3. Review
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.

Yixian You *Center of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.
Xiong Pei *Center of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.
Wei JiangCenter of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.
Qingmin ZengCenter of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.
Lang BaiCenter of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.
Taoyou ZhouCenter of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.
Xiaoju LvCenter of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.
Hong TangCenter of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.
Dongbo WuCenter of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Data on risk of developing chronic kidney disease (CKD) between non-obese and obese non-alcoholic fatty liver disease (NAFLD) patients are limited. We aimed to reveal the risk difference of incident CKD between non-obese and obese NAFLD patients. Methods: We searched PubMed, Embase, and Web of Science databases for studies which reported the incidence of CKD in non-obese and obese NAFLD from inception to 10 March 2024. The primary and secondary outcomes were pooled. Subgroup analysis was used to examine the heterogeneity. Results: A total of 15 studies were incorporated. The incidence of CKD in non-obese and obese NAFLD were 1,450/38,720 (3.74%) and 3,067/84,154 (3.64%), respectively. Non-obese NAFLD patients had a comparable risk of CKD as obese NAFLD (odds ratio [OR] 0.92, 95% confidence interval [95% CI] [0.72-1.19], I Conclusions: Non-obese NAFLD patients experienced the same risk of CKD compared to obese NAFLD.

Indexed as

Non-alcoholic Fatty Liver DiseaseObesityRenal Insufficiency, ChronicGlomerular Filtration RateHumansIncidenceRisk FactorsCKDCreatinineeGFRNAFLDNon-obese

Identifiers

PMID39713133
PMCPMC11660860

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.