Evidence map›Paper›PMID 39076541›Full record

ArticleReviews in cardiovascular medicine2024

Inflammation Links Cardiac Injury and Renal Dysfunction: A Cardiovascular Magnetic Resonance Study.

Xiaohui Xie, Jiahong Chen, Lei Yu, Jianzhong Sun, Chengchen Zhao, Qingqing Duan

Abstract read
In one paragraph

Article in Reviews in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Xiaohui XieDepartment of Nephrology, Zhejiang Hospital, 310009 Hangzhou, Zhejiang, China.
Jiahong ChenDepartment of Nephrology, Xiamen Hongai Hospital, 361000 Xiamen, Fujian, China.
Lei YuDepartment of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310009 Hangzhou, Zhejiang, China.
Jianzhong SunDepartment of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310009 Hangzhou, Zhejiang, China.
Chengchen ZhaoDepartment of Cardiovascular disease, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310009 Hangzhou, Zhejiang, China.
Qingqing DuanDepartment of Nephrology, Zhejiang Hospital, 310009 Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Inflammation is essential in cardiorenal syndrome, however there is still a lack of evidence proving the interaction between cardiac injury, renal dysfunction and the inflammatory response. This study aimed to illustrate the association between renal dysfunction and cardiac injury with a specific focus on the role of inflammation. Methods: A single-center, retrospective study included patients with heart failure admitted to the cardiovascular department from September 2019 to April 2022. Patients received cardiovascular magnetic resonance (CMR) imaging (T1 mapping and late gadolinium enhancement (LGE)). Demographic, creatinine and native T1 were analyzed using pearson correlation, linear regression and adjusted for confounders. Interaction and subgroup analysis were performed. Results: Finally, 50 validated heart failure (HF) patients (age 58.5 Conclusions: Kidney dysfunction was associated with cardiac injury and inflammation, respectively. The interaction between myocardial injury and kidney dysfunction is contingent on the severity of the inflammatory response. Further studies were needed to identify the mechanisms of the inflammatory response in cardiorenal syndrome.

Indexed as

cardiorenal syndromecardiovascular magnetic resonanceheart failureinflammationT1 mapping

Identifiers

PMID39076541
PMCPMC11263989

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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.