Evidence map›Paper›PMID 32583160›Full record

ReviewClinical and experimental nephrology2020

The need for disruptive innovation in acute kidney injury.

Kent Doi

Open access · hybridAbstract readReview
In one paragraph

Review in Clinical and experimental nephrology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Biomarkers of acute kidney injury: time to learn from implementations.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2021
    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

1 author at 1 institution in 1 country.

Kent DoiDepartment of Emergency and Critical Care Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, 113-8655, Japan. kdoi-tky@umin.ac.jp.ORCID http://orcid.org/0000-0002-0115-1439
The University of Tokyo · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute kidney injury (AKI) is a threatening medical condition associated with poor outcomes at different settings. The development of standardized diagnostic criteria and new biomarkers addressed significant clinical impacts of AKI and the need for an early AKI detection, respectively. There have been some breakthroughs in understanding the pathogenesis of AKI through basic research; however, treatments against AKI aside from renal replacement therapy (RRT) have not shown adequate successful results. Biomarkers that could identify good responders to certain treatment are expected to facilitate translation of basic research findings. Most patients with severe AKI treated with RRT died due to multiple-organ failure, not renal dysfunction. Hence, it is essential to identify other organ dysfunctions induced by AKI as organ crosstalk. Also, a multidisciplinary approach of critical care nephrology is needed to evaluate a complex organ crosstalk in AKI. For disruptive innovation for AKI, we further explore these new aspects of AKI, which previously were considered outside the scope of nephrology.

Indexed as

Acute Kidney InjuryAnimalsBiomarkersBiomedical ResearchCreatinineCritical CareDisease Models, AnimalFatty Acid-Binding ProteinsHumansInventionsLipocalin-2Renal Replacement TherapyUrineBiomarkersCreatinineFABP1 protein, humanFatty Acid-Binding ProteinsLCN2 protein, humanLipocalin-2Animal modelBiomarkerCritical care nephrologyOrgan crosstalk

Identifiers

PMID32583160
PMCPMC7524820
OpenAlexW3037007500

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.