Evidence map›Paper›PMID 34541359›Full record

ArticleHeliyon2021

Tissue inhibitor metalloproteinase 2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) best predicts the development of acute kidney injury.

Samuel Asamoah Sakyi, Richard K Dadzie Ephraim, Prince Adoba, Benjamin Amoani, Tonnies Buckman, Richard Mantey, Benjamin A Eghan

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 27 citations in OpenAlex.

  1. Pooled it
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  9. Tissue Inhibitors of Metalloproteinase 1 (TIMP-1) and 3 (TIMP-3) as New Markers of Acute Kidney Injury After Massive Burns.Medical science monitor : international medical journal of experimental and clinical research · 2024
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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 3 institutions in 1 country.

Samuel Asamoah SakyiDepartment of Molecular Medicine, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Ghana.
Richard K Dadzie EphraimDepartment of Medical Laboratory Science, School of Allied Health Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, Ghana.
Prince AdobaDepartment of Molecular Medicine, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Ghana.
Benjamin AmoaniDepartment of Biomedical Sciences, College of Health and Allied Sciences, School of Allied Health Sciences, University of Cape Coast, Cape Coast, Ghana.
Tonnies BuckmanDepartment of Molecular Medicine, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Ghana.
Richard ManteyDepartment of Molecular Medicine, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Ghana.
Benjamin A EghanDepartment of Medicine, School of Medical Sciences, Komfo Anokye Teaching Hospital, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Ghana.
Kwame Nkrumah University of Science and Technology · GHUniversity of Cape Coast · GHKomfo Anokye Teaching Hospital · GH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute kidney injury (AKI) is routinely diagnosed by creatinine-based guidelines, which is sub-optimal marker after injury due to renal and non-renal factors. This has necessitated the need for more specific and sensitive biomarkers for early detection of AKI in at risk patients. This prospective cross-sectional study used the biomarkers of cell cycle arrest and Neutrophil Gelatinase Associated Lipocalin (NGAL) to assess AKI among hospitalized patients.

methodsWe conveniently enrolled 151 in-patients at the Trauma and Specialist Hospital, Winneba in Ghana. Socio-demographic and clinical information were collected using structured questionnaires. Blood samples were collected for the estimation of serum creatinine, and AKI diagnosed and staged using the KDIGO guideline. Fresh urine samples were collected and urinary NGAL, TIMP-2 (tissue inhibitor metalloproteinase 2) and IGFBP-7 (insulin-like growth factor binding protein 7) were estimated using ELISA kits.

resultsThe cell cycle arrest biomarkers and NGAL were significantly (P < 0.001) higher among participants with AKI than those without AKI. [TIMP-2]∗[IGFBP-7] showed the best diagnostic performance (AUC = 0.94, CI = 0.90-0.98) followed by [IGFBP-7]∗NGAL] (AUC = 0.93, CI = 0.87-0.99), with NGAL having the least (AUC = 0.62, CI = 0.46-0.78). The cut-off for [TIMP-2]∗[IGFBP-7] showed the best predictive ability (95.8% sensitivity, 77.2% specificity, 44.2% PPV and 99% NPV). The cut-off for NGAL, on the other hand, showed the least predictive ability (62.5% sensitivity, 42.5% specificity, 17.0% PPV and 85.7% NPV).

conclusionTissue inhibitor metalloproteinase 2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) best predicts the development of AKI, and can be used in high risk patients for early diagnosis of AKI.

Indexed as

Acute kidney injuryBiomarkerUrinary NGALUrinary [TIMP-2]∗[IGFBP-7]

Identifiers

PMID34541359
PMCPMC8436126
OpenAlexW3198659601

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.