Evidence map›Paper›PMID 27495237›Full record

ArticleBMC nephrology2016

Clinical outcomes associated with albuminuria in central Australia: a cohort study.

Rebecca Ritte, Joanne Luke, Craig Nelson, Alex Brown, Kerin O'Dea, Alicia Jenkins, James D Best, Robyn McDermott, Mark Daniel, Kevin Rowley

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

Article in BMC nephrology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
0.7field-weighted citation impact, top 28% 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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Review
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

10 authors at 7 institutions in 2 countries.

Rebecca RitteOnemda Group, Indigenous Health Equity Unit, Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, VIC, Melbourne, 3010, Australia. rebecca.ritte@unimelb.edu.au.
Joanne LukeOnemda Group, Indigenous Health Equity Unit, Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, VIC, Melbourne, 3010, Australia.
Craig NelsonWestern Health, Footscray, VIC, 3011, Australia.
Alex BrownSouth Australian Health and Medical Research Institute, Adelaide, SA, 5000, Australia.
Kerin O'DeaMelbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia.
Alicia JenkinsNHMRC Clinical Trials Centre, University of Sydney, Camperdown, NSW, 1450, Australia.
James D BestFaculty of Medicine Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC, 3010, Australia.
Robyn McDermottCentre for Chronic Disease Prevention, James Cook University, Cairns, QLD, 4870, Australia.
Mark DanielSchool of Population Health, University of South Australia, Adelaide, SA, 5000, Australia.
Kevin RowleyOnemda Group, Indigenous Health Equity Unit, Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, VIC, Melbourne, 3010, Australia.
University of Melbourne · AUFootscray Hospital · AUJames Cook University · AUNanyang Technological University · SGSouth Australian Health and Medical Research Institute · AUUniversity of South Australia · AUUniversity of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic kidney disease (CKD) and end-stage-kidney disease (ESKD) continue to be under-diagnosed and a major burden for Aboriginal communities in central Australia. The aim of this study was to examine the risk of poor clinical outcomes associated with elevated albumin-to-creatinine ratio (ACR) among Aboriginal people in central Australia.

methodsCox proportional hazards models were used to estimate the risk of end stage kidney disease (ESKD), dialysis, CVD (cardiovascular disease) and mortality associated with participants' baseline albuminuria reading from a 10-year cohort study of Aboriginal people (n = 623) from three communities in central Australia. Predictors of progression of albuminuria were also examined in the context of the Kidney Health Australia (KHA) Risk Matrix.

resultsA baseline ACR level of ≥3.5 mg/mmol was associated with an almost 10-fold increased risk of ESKD (95%CI 2.07-43.8) and a 15-fold risk of dialysis (95%CI 1.89-121). Albuminuria ≥3.5 mg/mmol was also associated with a borderline 63 % increased risk of CVD (95%CI 0.98-2.71). No significant association was observed with mortality from all-causes or chronic disease. Diabetes and a waist-to-hip ratio ≥0.90 independently predicted a two-fold increased risk of a progression to higher ACR levels.

conclusionsA single measure of moderately increased albuminuria was a strong predictor of renal failure in this population. A single spot urine ACR analysis in conjunction with the KHA Risk Matrix may be a useful and efficient strategy to screen for risk of CKD and progression to dialysis in remote communities. A focus on individuals with diabetes and/or central obesity for strategies to avoid increases in albuminuria may also prevent future CKD and CVD complications.

Indexed as

AdolescentAdultAgedAged, 80 and overAlbuminuriaAustraliaCardiovascular DiseasesCreatinineDiabetes MellitusDisease ProgressionFemaleHumansKidney Failure, ChronicLongitudinal StudiesMaleMiddle AgedCreatinineAboriginal peopleAlbumin creatinine ratioAlbuminuriaCohort studyEnd stage renal diseaseRiskRural and remote health

Identifiers

PMID27495237
PMCPMC4974695
OpenAlexW2484951638

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.