Evidence map›Paper›PMID 34261422›Full record

ArticleRenal failure2021

Early prediction of acute kidney injury after liver transplantation by scoring system and decision tree.

Wang Xin, Wang Yi, Hui Liu, Liu Haixia, Lin Dongdong, Yingmin Ma, Guangming Li

Open access · goldAbstract read
In one paragraph

Article in Renal failure, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 9% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 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

7 authors at 2 institutions in 1 country.

Wang XinDepartment of Intensive Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Wang YiDepartment of Intensive Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Hui LiuDepartment of Pharmacy, Beijing Haidian Hospital, Beijing, China.
Liu HaixiaDepartment of Intensive Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Lin DongdongDepartment of General Surgery, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Yingmin MaDepartment of Respiratory and Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Guangming LiDepartment of General Surgery, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Capital Medical University · CNBeijing Haidian Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsEarly detection of acute kidney injury (AKI) is crucial for the prognosis of patients after liver transplantation (LT). This passage aims to analyze the perioperative clinical markers of AKI after LT and establish predictive models based on clinical variables for early detection of AKI after LT.

methodsWe prospectively collected 109 patients with LT, and compared the differences of perioperative clinical markers between the AKI group and non-AKI group. The scoring system and decision tree model were established through the risk factors. Another 163 patients who underwent LT in the same center from 2017 to 2018 were retrospectively collected to verify the models.

resultsIn multiple comparisons of risk factors of post-LT AKI, pre-operative factors were excluded automatically, intraoperative and post-operative factors including operating time, intraoperative hypotension time, post-operative infection, the peak of post-operative AST, and post-operative shock were the independent risk factors for post-LT AKI. The scoring system established with the risk factors has good predictive power (AUC = 0.755) in the validation cohort. The decision tree also shows that post-operative shock was the most important marker, followed by post-operative infection.

conclusionFive intraoperative and post-operative factors are independently associated with post-LT AKI rather than pre-operative factors, which indicates that operation technique and post-operative management may more important for the prevention of post-LT AKI. The scoring system and decision tree model could complement each other, and provide quantitative and intuitive prediction tools for clinical practice of early detection of post-LT AKI.

Indexed as

Decision TreesAcute Kidney InjuryAdultFemaleHumansHypotensionLiver TransplantationLogistic ModelsMaleMiddle AgedMultivariate AnalysisRetrospective StudiesRisk AssessmentRisk FactorsAKI after LTdecision treeearly detectionscoring system

Identifiers

PMID34261422
PMCPMC8281092
OpenAlexW3182175433

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.