Evidence map›Paper›PMID 28778358›Full record

ReviewAdvances in chronic kidney disease2017

Epidemiology of AKI: Utilizing Large Databases to Determine the Burden of AKI.

Simon Sawhney, Simon D Fraser

Abstract readReview
In one paragraph

Review in Advances in chronic kidney disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 3 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

93 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
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  9. Observational
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  12. Review
  13. Mitophagy Regulates Kidney Diseases.Kidney diseases (Basel, Switzerland) · 2024
    Review
  14. Observational
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  16. Review
  17. Article
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  20. Recovery of kidney function after acute kidney disease-a multi-cohort analysis.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
    Article

33 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

2 authors.

Simon SawhneyKidney Disease@Farr Collaboration, University of Aberdeen, Aberdeen, UK; and Kidney Disease@Farr Collaboration, University of Southampton, Southampton, UK. Electronic address: simon.sawhney@abdn.ac.uk.
Simon D FraserKidney Disease@Farr Collaboration, University of Aberdeen, Aberdeen, UK; and Kidney Disease@Farr Collaboration, University of Southampton, Southampton, UK.

Funding

Arthritis Research UKBritish Heart FoundationCancer Research UKChief Scientist OfficeMedical Research Council MC_PC_13040Medical Research Council MR/K007017/1Medical Research Council MR/M501633/1Medical Research Council MR/M501633/2Wellcome TrustWellcome Trust 102729/Z/13/Z
6 · The paper itself

Abstract

Large observational databases linking kidney function and other routine patient health data are increasingly being used to study acute kidney injury (AKI). Routine health care data show an apparent rise in the incidence of population AKI and an increase in acute dialysis. Studies also report an excess in mortality and adverse renal outcomes after AKI, although with variation depending on AKI severity, baseline, definition of renal recovery, and the time point during follow-up. However, differences in data capture, AKI awareness, monitoring, recognition, and clinical practice make comparisons between health care settings and periods difficult. In this review, we describe the growing role of large databases in determining the incidence and prognosis of AKI and evaluating initiatives to improve the quality of care in AKI. Using examples, we illustrate this use of routinely collected health data and discuss the strengths, limitations, and implications for researchers and clinicians.

Indexed as

Databases, FactualAcute Kidney InjuryCreatinineGlomerular Filtration RateHumansIncidenceInternational Classification of DiseasesPrognosisTime FactorsTreatment OutcomeCreatinineAcute kidney injuryBig-dataIncidencePrognosisQuality improvement

Identifiers

PMID28778358
PMCPMC5648688

What OpenQuestion holds

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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.