Evidence map›Paper›PMID 35402585›Full record

ArticleAnnals of translational medicine2022

Risk factors of renal replacement therapy after heart transplantation: a retrospective single-center study.

Bingying Xie, Lei Fu, Yijin Wu, Xinfu Xie, Wenhao Zhang, Jihua Hou, Dinglin Liu, Ruizhao Li, Li Zhang, Chengbin Zhou and 4 more

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2022. 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
1.5field-weighted citation impact, top 19% of its field
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, 7 citations in OpenAlex.

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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

14 authors at 5 institutions in 1 country.

Bingying Xie *Department of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Lei Fu *Department of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Yijin WuDepartment of Intensive Care Unit of Cardiac Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Xinfu XieDepartment of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Wenhao ZhangDepartment of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Jihua HouDepartment of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Dinglin LiuDepartment of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Ruizhao LiDepartment of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Li ZhangDepartment of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Chengbin ZhouHeart Transplantation and VAD Division, Department of Cardiovascular Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Jinsong HuangHeart Transplantation and VAD Division, Department of Cardiovascular Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Xinling LiangDepartment of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Min WuHeart Transplantation and VAD Division, Department of Cardiovascular Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Zhiming YeDepartment of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Guangdong Academy of Medical Sciences · CNGuangdong Provincial People's Hospital · CNShantou University · CNSouth China University of Technology · CNSouthern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Acute kidney injury (AKI) and renal replacement therapy (RRT) are common after heart transplantation (HT). The need for RRT has been reported to be one of the most important predictors of a poor prognosis after HT. Therefore, it is important to early identify risk factors of RRT after HT. However, in the heart transplantation setting, the risk factors are less well studied, and some of the conclusions are controversial. This study aimed to identify the clinical predictors of RRT after HT. Methods: This single-center, retrospective study from January 2010 to June 2021 analyzed risk factors (pre-, intra-, and postoperative characteristics) of 163 patients who underwent HT. The endpoint of the study was RRT within 7 days of HT. Risk factors were analyzed by multivariable logistic regression models. Results: Fifty-five (33.74%) recipients required RRT within 7 days of HT. Factors independently associated with RRT after HT were as follows: a baseline estimated glomerular filtration rate (eGFR) <60 mL/min per 1.73 m Conclusions: A low preoperative eGFR, a high intraoperative dose of methylprednisolone, a long CPB time, the use of mechanical circulatory support, and a high postoperative TBIL were risk factors for RRT after HT. While a high postoperative serum albumin level and a high left ventricular ejection fraction were protective factors. Understanding these risk factors may help us identify high-risk patients and intervene early.

Indexed as

acute kidney injury (AKI)Heart transplantation (HT)renal replacement therapy (RRT)

Identifiers

PMID35402585
PMCPMC8987878
OpenAlexW4220785011

What Socratic holds

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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 Socratic graph.