Evidence map›Paper›PMID 34716482›Full record

ArticlePediatric nephrology (Berlin, Germany)2022

Comparing the pRIFLE, AKIN, KDIGO, and modified KDIGO criteria in neonates after cardiac surgery.

Chao Lu, Jiaxin Lian, Zhongming Cao, Liwen Chen, Jiexian Liang, Sheng Wang

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In one paragraph

Article in Pediatric nephrology (Berlin, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
0.6field-weighted citation impact, top 33% 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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Implementation Strategies for Baby NINJA (Nephrotoxic Injury Negated by Just-in-Time Action) to Prevent Neonatal Medication-Induced Kidney Injury.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2023
    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 at 1 institution in 1 country.

Chao LuDepartment of Anesthesiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Jiaxin LianDepartment of Anesthesiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Zhongming CaoDepartment of Anesthesiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Liwen ChenDepartment of Anesthesiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Jiexian LiangDepartment of Anesthesiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Sheng WangDepartment of Anesthesiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China. shengwang_gz@163.com.
Guangdong Provincial People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhile several standardized criteria for acute kidney injury (AKI) have been studied, there is no consensus on which criteria to use in neonates after cardiac surgery. The goal of this research was to compare the AKI incidence and outcomes according to the pediatric Risk, Injury, Failure and Loss, and End-Stage (pRIFLE), AKI Network (AKIN), Kidney Disease Improving Global Outcomes (KDIGO), and modified KDIGO (mKDIGO) criteria in neonates following congenital cardiac surgery.

methodsA clinical database of all neonates undergoing congenital cardiac surgery admitted to the Cantonese cardiac center from 2014 to 2020 was retrospectively analyzed. AKI was based on the pRIFLE, AKIN, KDIGO, and mKDIGO classification. The predictive abilities for postoperative outcomes were compared by receiver operating curves, and multivariate logistic regression analysis was used to assess the association of AKI definitions with postoperative outcomes.

resultsIn the study population of 522 patients, 177, 110, 131, and 114 neonates had AKI according to the pRIFLE, AKIN, KDIGO, and mKDIGO criteria, respectively. After multivariate analysis, all definitions were found to be significant predictors of increased mortality. The AUCs for mortality were substantially different with pRIFLE (AUC, 0.795), AKIN (AUC, 0.724), KDIGO (AUC, 0.819), and mKDIGO (AUC, 0.831) (P < 0.01) across the entire population, whereas the mKDIGO system was more accurate than the pRIFLE, AKIN, and KDIGO systems.

conclusionsThe incidence of AKI varied across all definitions. However, the mKDIGO system was more accurate in predicting in-hospital mortality than the pRIFLE, AKIN, and KDIGO systems in neonates after heart surgery.

Indexed as

Acute Kidney InjuryCardiac Surgical ProceduresChildHospital MortalityHumansInfant, NewbornKidneyRetrospective StudiesRisk FactorsAcute kidney injuryMortalityNeonatal cardiac surgeryPrediction

Identifiers

PMID34716482
OpenAlexW3211057586

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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.