Evidence map›Paper›PMID 36371256›Full record

SynthesisCritical care (London, England)2022

Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis.

Heng-Chih Pan, Shao-Yu Yang, Terry Ting-Yu Chiou, Chih-Chung Shiao, Che-Hsiung Wu, Chun-Te Huang, Tsai-Jung Wang, Jui-Yi Chen, Hung-Wei Liao, Sheng-Yin Chen and 8 more

2 registry-linked trialsOpen access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Critical care (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 64 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 4 pooled it
11.7field-weighted citation impact, top 1% 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.

NCT05721638 completednot on this mapstarted 2023, after this paper: background citation

Efficacy of Serum and Urinary Neutrophil Gelatinase-associated Lipocalin in the Early Detection of Acute Kidney Injury After Major Abdominal Surgery

TypeobservationalSponsorAntalya Training and Research HospitalRan2023 to 2023Enrolled43ConditionsAcute Kidney InjuryArmsNeutrophil gelatinase-associated lipocalin
NCT06386796 recruitingnot on this mapstarted 2024, after this paper: background citation

Renal Resistive Index as a Predictor of Acute Renal Impairment in High-risk Patients Admitted to Surgical Intensive Care Unit.

TypeobservationalSponsorAswan UniversityRan2024 to 2026Enrolled100ConditionsAcute Kidney Injury, Critical Illness
3 · Its place in the literature

Who cites it

64 citing papers in PubMed, 4 syntheses or guidelines pooled it, 97 citations in OpenAlex.

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4 more citing papers are in PubMed but not listed here.

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

18 authors at 9 institutions in 2 countries.

Heng-Chih PanGraduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
Shao-Yu YangGraduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
Terry Ting-Yu ChiouChang Gung University College of Medicine, Taoyuan, Taiwan.
Chih-Chung ShiaoNSARF (National Taiwan University Hospital Study Group of ARF) and CAKS (Taiwan Consortium for Acute Kidney Injury and Renal Diseases), Taipei, Taiwan.
Che-Hsiung WuNSARF (National Taiwan University Hospital Study Group of ARF) and CAKS (Taiwan Consortium for Acute Kidney Injury and Renal Diseases), Taipei, Taiwan.
Chun-Te HuangDepartment of Critical Care Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.
Tsai-Jung WangDepartment of Critical Care Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.
Jui-Yi ChenDivision of Nephrology, Department of Internal Medicine, Chi Mei Medical Center, Tainan, Taiwan.
Hung-Wei LiaoDivision of Nephrology, Department of Internal Medicine, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.
Sheng-Yin ChenHarvard T.H. Chan School of Public Health, Boston, MA, USA.
Tao-Min HuangDivision of Nephrology, Department of Internal Medicine, National Taiwan University Hospital, Room 1419, Clinical Research Building, 7 Chung-Shan South Road, Taipei, 100, Taiwan.
Ya-Fei YangEveran Hospital, Taichung, Taiwan.
Hugo You-Hsien LinNSARF (National Taiwan University Hospital Study Group of ARF) and CAKS (Taiwan Consortium for Acute Kidney Injury and Renal Diseases), Taipei, Taiwan.
Ming-Jen ChanNSARF (National Taiwan University Hospital Study Group of ARF) and CAKS (Taiwan Consortium for Acute Kidney Injury and Renal Diseases), Taipei, Taiwan.
Chiao-Yin SunDivision of Nephrology, Department of Internal Medicine, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan.
Yih-Ting ChenDivision of Nephrology, Department of Internal Medicine, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan.
Yung-Chang ChenChang Gung University College of Medicine, Taoyuan, Taiwan.
Vin-Cent WuDivision of Nephrology, Department of Internal Medicine, National Taiwan University Hospital, Room 1419, Clinical Research Building, 7 Chung-Shan South Road, Taipei, 100, Taiwan. q91421028@ntu.edu.tw.
National Taiwan University Hospital · TWChang Gung University · TWKeelung Chang Gung Memorial Hospital · TWLinkou Chang Gung Memorial Hospital · TWTaichung Veterans General Hospital · TWChi Mei Medical Center · TWChina Medical University Hospital · TWHarvard University · USWan Fang Hospital · TW

Funding

Ministry of Science and Technology (MOST) of the Republic of China (Taiwan) MOST 106-2321-B-182-002Ministry of Science and Technology (MOST) of the Republic of China (Taiwan) MOST 107-2321-B-182-004Ministry of Science and Technology (MOST) of the Republic of China (Taiwan) MOST 108-2321-B-182-003Ministry of Science and Technology (MOST) of the Republic of China (Taiwan) MOST 109-2321-B-182-001National Health Research Institutes PH-102-SP-09National Science Council 104-2314-B-002-125-MY3National Science Council 106-2314-B-002 -166 -MY3National Science Council 107-2314-B-002-026-MY3National Taiwan University Hospital 106-FTN20National Taiwan University Hospital 106-P02National Taiwan University Hospital 106-S3582National Taiwan University Hospital 107-S3809National Taiwan University Hospital 107-T02National Taiwan University Hospital 109-S4634National Taiwan University Hospital PC1246National Taiwan University Hospital UN106-014National Taiwan University Hospital UN109-041National Taiwan University Hospital VN109-09
6 · The paper itself

Abstract

backgroundSeveral biomarkers have been proposed to predict the occurrence of acute kidney injury (AKI); however, their efficacy varies between different trials. The aim of this study was to compare the predictive performance of different candidate biomarkers for AKI.

methodsIn this systematic review, we searched PubMed, Medline, Embase, and the Cochrane Library for papers published up to August 15, 2022. We selected all studies of adults (> 18 years) that reported the predictive performance of damage biomarkers (neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid-binding protein (L-FABP)), inflammatory biomarker (interleukin-18 (IL-18)), and stress biomarker (tissue inhibitor of metalloproteinases-2 × insulin-like growth factor-binding protein-7 (TIMP-2 × IGFBP-7)) for the occurrence of AKI. We performed pairwise meta-analyses to calculate odds ratios (ORs) and 95% confidence intervals (CIs) individually. Hierarchical summary receiver operating characteristic curves (HSROCs) were used to summarize the pooled test performance, and the Grading of Recommendations, Assessment, Development and Evaluations criteria were used to appraise the quality of evidence.

resultsWe identified 242 published relevant studies from 1,803 screened abstracts, of which 110 studies with 38,725 patients were included in this meta-analysis. Urinary NGAL/creatinine (diagnostic odds ratio [DOR] 16.2, 95% CI 10.1-25.9), urinary NGAL (DOR 13.8, 95% CI 10.2-18.8), and serum NGAL (DOR 12.6, 95% CI 9.3-17.3) had the best diagnostic accuracy for the risk of AKI. In subgroup analyses, urinary NGAL, urinary NGAL/creatinine, and serum NGAL had better diagnostic accuracy for AKI than urinary IL-18 in non-critically ill patients. However, all of the biomarkers had similar diagnostic accuracy in critically ill patients. In the setting of medical and non-sepsis patients, urinary NGAL had better predictive performance than urinary IL-18, urinary L-FABP, and urinary TIMP-2 × IGFBP-7: 0.3. In the surgical patients, urinary NGAL/creatinine and urinary KIM-1 had the best diagnostic accuracy. The HSROC values of urinary NGAL/creatinine, urinary NGAL, and serum NGAL were 91.4%, 85.2%, and 84.7%, respectively.

conclusionsBiomarkers containing NGAL had the best predictive accuracy for the occurrence of AKI, regardless of whether or not the values were adjusted by urinary creatinine, and especially in medically treated patients. However, the predictive performance of urinary NGAL was limited in surgical patients, and urinary NGAL/creatinine seemed to be the most accurate biomarkers in these patients. All of the biomarkers had similar predictive performance in critically ill patients. Trial registration CRD42020207883 , October 06, 2020.

Indexed as

Acute Kidney InjuryInterleukin-18AdultBiomarkersCreatinineHospitalsHumansLipocalin-2Tissue Inhibitor of Metalloproteinase-2BiomarkersCreatinineInterleukin-18Lipocalin-2Tissue Inhibitor of Metalloproteinase-2Acute kidney injuryBiomarkerCritically ill patientNeutrophil gelatinase-associated lipocalin

Identifiers

PMID36371256
PMCPMC9652605
OpenAlexW4309045920

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.