Evidence map›Paper›PMID 32938443›Full record

ArticleBMC medical informatics and decision making2020

How to optimize the design and implementation of risk prediction tools: focus group with patients with IgA nephropathy.

Anna R Gagliardi, Heather N Reich, Daniel C Cattran, Sean J Barbour

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 84% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 1 country.

Anna R GagliardiUniversity Health Network, Toronto, Canada. anna.gagliardi@uhnresearch.ca.ORCID 0000-0002-5721-809X
Heather N ReichUniversity Health Network, Toronto, Canada.
Daniel C CattranUniversity Health Network, Toronto, Canada.
Sean J BarbourUniversity of British Columbia, Vancouver, Canada.
University Health Network · CAUniversity of British Columbia · CA

Funding

CIHR
6 · The paper itself

Abstract

backgroundIgA nephropathy (IgAN) is a common type of chronic immune-mediated kidney disease with variable risk of progression to end-stage kidney disease. Risk stratification helps clinicians weight the potential risks and benefits of immunosuppressive therapy for individual patients, and can inform patient-centred communication. No prior research examined barriers of risk predication tools (RPT) specific to IgAN. The purpose of this study was to explore determinants (facilitators, barriers) of RPT use from the patient perspective.

methodsWe conducted a single focus group with English-speaking adults aged 18 or older with biopsy-proven IgAN. We asked about how they would use an IgAN RPT, and how to improve its design and implementation. We analyzed the transcript using constant comparison to inductively derive themes, and complied with qualitative research reporting criteria.

resultsThe 5 participants were Caucasian men who varied in age from 35 to 55. The glomerular filtration rate ranged from 29 to 71 mL/min/1.73m

conclusionsPatients with IgAN identified numerous ways to enhance the design and use of an RPT. Others could use this information to design and implement RPTs for patients with other conditions, but should employ user-centred design to develop RPTs that address patient preferences.

Indexed as

Glomerulonephritis, IGAKidney Failure, ChronicAdultFocus GroupsForecastingGlomerular Filtration RateHumansMaleMiddle AgedProteinuriaRiskChronic kidney diseaseIgA nephropathyPatient-centred carePatient-provider communicationQualitative researchRisk prediction calculatorUser-centred design

Identifiers

PMID32938443
PMCPMC7493917
OpenAlexW3086321806

What OpenQuestion holds

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LicenceCC BY
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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.