Evidence map›Paper›PMID 29042386›Full record

Trial reportBMJ open2017

Effectiveness of an electronic patient-centred self-management tool for gout sufferers: a cluster randomised controlled trial protocol.

Richard O Day, Lauren J Frensham, Amy D Nguyen, Melissa T Baysari, Eindra Aung, Annie Y S Lau, Nicholas Zwar, Jennifer Reath, Tracey Laba, Ling Li and 12 more

Open access · goldAbstract readMulticenter StudyRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

10 citing papers in PubMed, 28 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. [Development and clinical application of the health education knowledge assessment questionnaire for gout].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2022
    Article
  7. Review
  8. Article
  9. Article
  10. 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

22 authors at 9 institutions in 2 countries.

Richard O DayDepartment of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia.ORCID 0000-0002-6045-6937
Lauren J FrenshamDepartment of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia.
Amy D NguyenDepartment of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia.
Melissa T BaysariDepartment of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia.
Eindra AungDepartment of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia.
Annie Y S LauCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Nicholas ZwarSchool of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, Australia.
Jennifer ReathSchool of Medicine, Western Sydney University, Sydney, Australia.
Tracey LabaThe George Institute for Global Health, Sydney Medical School, The University of Sydney, Sydney, Australia.ORCID 0000-0002-5182-9092
Ling LiCentre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Andrew McLachlanFaculty of Pharmacy and Centre for Education and Research on Ageing, University of Sydney, Sydney, Australia.
William B RuncimanSchool of Health Sciences, University of South Australia, Adelaide, Australia.
Rachelle BuchbinderMonash Department of Clinical Epidemiology, Cabrini Institute and Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Robyn Clay-WilliamsCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Enrico CoieraCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.ORCID 0000-0002-6444-6584
Jeffrey BraithwaiteCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
H Patrick McNeilCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
David J HunterInstitute of Bone and Joint Research, Kolling Institute, Sydney Medical School, The University of Sydney, Sydney, Australia.ORCID 0000-0003-3197-752X
Kevin D PileDepartment of Medicine, Western Sydney University, Sydney, Australia.
Ian PortekSt George and Sutherland Clinical School, Faculty of Medicine, University of New South Wales, Sydney, Australia.
Kenneth Mapson WIlliamsDepartment of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, Australia.
Johanna I WestbrookCentre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Macquarie University · AUUNSW Sydney · AUThe University of Sydney · AUCabrini Hospital · AUCamden and Campbelltown Hospitals · AUSt Vincent's Hospital Melbourne · AUSutherland Hospital · AUUniversity of South Australia · AUWestern Sydney University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGout is increasing despite effective therapies to lower serum urate concentrations to 0.36 mmol/L or less, which, if sustained, significantly reduces acute attacks of gout. Adherence to urate-lowering therapy (ULT) is poor, with rates of less than 50% 1 year after initiation of ULT. Attempts to increase adherence in gout patients have been disappointing. We aim to evaluate the effectiveness of use of a personal, self-management, 'smartphone' application (app) to achieve target serum urate concentrations in people with gout. We hypothesise that personalised feedback of serum urate concentrations will improve adherence to ULT. METHODS AND ANALYSIS: Setting and designPrimary care. A prospective, cluster randomised (by general practitioner (GP) practices), controlled trial.

participantsGP practices will be randomised to either intervention or control clusters with their patients allocated to the same cluster.

interventionThe intervention group will have access to the Healthy.me app tailored for the self-management of gout. The control group patients will have access to the same app modified to remove all functions except the Gout Attack Diary. PRIMARY AND SECONDARY OUTCOMES: The proportion of patients whose serum urate concentrations are less than or equal to 0.36 mmol/L after 6 months. Secondary outcomes will be proportions of patients achieving target urate concentrations at 12 months, ULT adherence rates, serum urate concentrations at 6 and 12 months, rates of attacks of gout, quality of life estimations and process and economic evaluations. The study is designed to detect a ≥30% improvement in the intervention group above the expected 50% achievement of target serum urate at 6 months in the control group: power 0.80, significance level 0.05, assumed 'dropout' rate 20%. ETHICS AND DISSEMINATION: This study has been approved by the University of New South Wales Human Research Ethics Committee. Study findings will be disseminated in international conferences and peer-reviewed journal. TRIAL REGISTRATION NUMBER: ACTRN12616000455460.

Indexed as

InternetResearch DesignAllopurinolGoutGout SuppressantsHumansPatient ComplianceProspective StudiesQuality of LifeSelf-ManagementUric AcidAllopurinolGout SuppressantsUric AcidAdherenceGoutSelf-management E-health Applications (apps)Urate

Identifiers

PMID29042386
PMCPMC5652564
OpenAlexW2765525273

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.