Evidence mapPaperPMID 28624882Full record

ReviewJournal of nephrology2018

Predicting acute kidney injury: current status and future challenges.

Simona Pozzoli, Marco Simonini, Paolo Manunta

Abstract readReview
In one paragraph

Review in Journal of nephrology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
field-weighted citation impact
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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. Time for Precision Medicine in the Diagnosis of Acute Kidney Injury.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2022
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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

3 authors.

Simona PozzoliChair of Nephrology - IRCCS San Raffaele Scientific Institute, Genomics of Renal Diseases and Hypertension Unit, Università Vita Salute San Raffaele, Via Olgettina 60, 20132, Milan, Italy.
Marco SimoniniChair of Nephrology - IRCCS San Raffaele Scientific Institute, Genomics of Renal Diseases and Hypertension Unit, Università Vita Salute San Raffaele, Via Olgettina 60, 20132, Milan, Italy. simonini.marco@hsr.it.
Paolo ManuntaChair of Nephrology - IRCCS San Raffaele Scientific Institute, Genomics of Renal Diseases and Hypertension Unit, Università Vita Salute San Raffaele, Via Olgettina 60, 20132, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute kidney injury (AKI) is characterized by an acute decline in renal function and is associated to increased mortality rate, hospitalization time, and total health-related costs. The severity of this 'fearsome' clinical complication might depend on, or even be worsened by, the late detection of AKI, when the diagnosis is based on the elevation of serum creatinine (SCr). For these reasons, in recent years a great number of new tools, biomarkers and predictive models have been proposed to clinicians in order to improve diagnosis and prevent the development of AKI. The purpose of this narrative paper is to review the current state of the art in prediction and early detection of AKI and outline future challenges.

Indexed as

Acute Kidney InjuryBiomarkersCystatin CEarly DiagnosisFatty Acid-Binding ProteinsGenetic Predisposition to DiseaseGenomicsHepatitis A Virus Cellular Receptor 1HumansInsulin-Like Growth Factor Binding ProteinsInterleukin-18Kidney Function TestsLipocalin-2Models, BiologicalOuabainRenal Insufficiency, ChronicBiomarkersCystatin CFatty Acid-Binding ProteinsHAVCR1 protein, humanHepatitis A Virus Cellular Receptor 1IL18 protein, humaninsulin-like growth factor binding protein-related protein 1Insulin-Like Growth Factor Binding ProteinsInterleukin-18Lipocalin-2OuabainTIMP2 protein, humanTissue Inhibitor of Metalloproteinase-2Acute kidney injuryBiomarkersGeneticsNew OMICsPrediction

Identifiers

PMID28624882
PMCPMC5829133

What Socratic 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 Socratic graph.