Evidence map›Paper›PMID 35677313›Full record

ArticlePractical laboratory medicine2022

Advances in laboratory detection of acute kidney injury.

Faeq Husain-Syed, Thiago Reis, Kianoush Kashani, Claudio Ronco

Open access · goldAbstract read
In one paragraph

Article in Practical laboratory medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
2.4field-weighted citation impact, top 11% 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

13 citing papers in PubMed, 2 syntheses or guidelines 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

4 authors at 4 institutions in 4 countries.

Faeq Husain-SyedDepartment of Internal Medicine II, University Hospital Giessen and Marburg, Justus-Liebig-University Giessen, Klinikstraße 33, 35392, Giessen, Germany.
Thiago ReisLaboratory of Molecular Pharmacology, Faculty of Health Sciences, University of Brasília, Brasília, Distrito Federal, Brazil.
Kianoush KashaniDivision of Nephrology and Hypertension, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
Claudio RoncoDepartment of Medicine (DIMED), Università di Padova, Via Giustiniani, 2-35128, Padua, Italy.
Mayo Clinic · USUniversidade de Brasília · BRUniversity of Giessen · DEUniversity of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances have improved our understanding of the epidemiology and pathophysiology of acute kidney injury (AKI). So far, the Kidney Disease: Improving Global Outcome guidelines define and stratify kidney injury based on increases in serum creatinine level and/or decreases in urine output. Although the term AKI acknowledges the existence of cellular injury, its diagnosis is still only defined by the reduced excretory function of the kidney. New biomarkers that aid a better understanding of the relationship between acute tubular injury and kidney dysfunction have been identified, reflecting the advances in molecular biology. The expression of some of these novel biomarkers precedes changes in conventional biomarkers or can increase their predictive power. Therefore, they might enhance the clinical accuracy of the definition of AKI. This review summarizes the limitations of the current AKI classification and a panel of candidate biomarkers for augmenting AKI classification and recognition of AKI subphenotypes. We expect that the integration of appropriately selected biomarkers in routine clinical practice can improve AKI care.

Indexed as

Acute kidney stressCell cycle arrest biomarkersSubclinical AKITubular damage

Identifiers

PMID35677313
PMCPMC9168173
OpenAlexW4281781849

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.