Evidence map›Paper›PMID 34933932›Full record

ArticleBMJ evidence-based medicine2022

Kidney trajectory charts to assist general practitioners in the assessment of patients with reduced kidney function: a randomised vignette study.

Michelle Guppy, Paul Glasziou, Elaine Beller, Richard Flavel, Jonathan E Shaw, Elizabeth Barr, Jenny Doust

Open access · hybridAbstract read
In one paragraph

Article in BMJ evidence-based medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 26% 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, 10 citations in OpenAlex.

  1. Prevalence of reduced eGFR in European adults using KDIGO and age-adapted eGFR thresholds.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025
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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

7 authors at 4 institutions in 1 country.

Michelle GuppyInstitute for Evidence-Based Healthcare, Bond University, Robina, Queensland, Australia mguppy2@une.edu.au.ORCID 0000-0001-7256-4938
Paul GlasziouInstitute for Evidence-Based Healthcare, Bond University, Robina, Queensland, Australia.
Elaine BellerInstitute for Evidence-Based Healthcare, Bond University, Robina, Queensland, Australia.
Richard FlavelSchool of Environmental and Rural Science, University of New England, Armidale, New South Wales, Australia.
Jonathan E ShawClinical Diabetes and Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Elizabeth BarrClinical Diabetes and Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Jenny DoustCentre for Longitudinal and Life Course Research, The University of Queensland, Herston, Queensland, Australia.ORCID 0000-0002-4024-9308
Bond University · AUBaker Heart and Diabetes Institute · AUThe University of Queensland · AUUniversity of New England · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the decisional impact of an age-based chart of kidney function decline to support general practitioners (GPs) to appropriately interpret estimated glomerular filtration rate (eGFR) and identify patients with a clinically relevant kidney problem. DESIGN AND

settingRandomised vignette study

participants372 Australian GPs from August 2018 to November 2018.

interventionGPs were given two patient case scenarios: (1) an older woman with reduced but stable renal function and (2) a younger Aboriginal man with declining kidney function still in the normal range. One group was given an age-based chart of kidney function to assist their assessment of the patient (initial chart group); the second group was asked to assess the patients without the chart, and then again using the chart (delayed chart group).

main outcome measuresGPs' assessment of the likelihood-on a Likert scale-that the patients had chronic kidney disease (CKD) according to the usual definition or a clinical problem with their kidneys.

resultsPrior to viewing the age-based chart GPs were evenly distributed as to whether they thought case 1-the older woman-had CKD or a clinically relevant kidney problem. GPs who had initial access to the chart were less likely to think that the older woman had CKD, and less likely to think she had a clinically relevant problem with her kidneys than GPs who had not viewed the chart. After subsequently viewing the chart, 14% of GPs in the delayed chart group changed their opinion, to indicate she was unlikely to have a clinically relevant problem with her kidneys.Prior to viewing the chart, the majority of GPs (66%) thought case 2-the younger man-did not have CKD, and were evenly distributed as to whether they thought he had a clinically relevant kidney problem. In contrast, GPs who had initial access to the chart were more likely to think he had CKD and the majority (72%) thought he had a clinically relevant kidney problem. After subsequently viewing the chart, 37% of GPs in the delayed chart group changed their opinion to indicate he likely had a clinically relevant problem with his kidneys.

conclusionsUse of the chart changed GPs interpretation of eGFR, with increased recognition of the younger male patient's clinically relevant kidney problem, and increased numbers classifying the older female patient's kidney function as normal for her age. This study has shown the potential of an age-based kidney function chart to reduce both overdiagnosis and underdiagnosis.

Indexed as

General PractitionersRenal Insufficiency, ChronicAgedAustraliaFemaleGlomerular Filtration RateHumansKidneyMaleclinical decision-makingdiagnosisgeneral practicenephrology

Identifiers

PMID34933932
PMCPMC9510425
OpenAlexW4200513056

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.