Evidence map›Paper›PMID 36713019›Full record

ArticleEuropean heart journal. Digital health2022

Universal Clinician Device for improving risk prediction and management of patients with atrial fibrillation: an assumed benefit analysis.

Georg van Husen, Saverio Virdone, Karen Pieper, Gloria Kayani, Keith A A Fox

Registry-linked trialAbstract read
In one paragraph

Article in European heart journal. Digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01090362 (Prospective, Multi Centre, International Registry of Male and Female Patients Newly Diagnosed With Atrial Fibrillation.), which is not on this 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
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.

NCT01090362 completednot on this map

Prospective, Multi Centre, International Registry of Male and Female Patients Newly Diagnosed With Atrial Fibrillation.

TypeobservationalSponsorThrombosis Research InstituteRan2009 to 2020Enrolled57,250ConditionsAtrial Fibrillation
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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

5 authors.

Georg van Husentenac.io, Oberwallstrasse 6, 10117 Berlin, Germany.ORCID https://orcid.org/0000-0001-8928-0712
Saverio VirdoneDepartment of Statistics, The Thrombosis Research Institute, London, UK.ORCID https://orcid.org/0000-0003-1849-6422
Karen PieperDepartment of Statistics, The Thrombosis Research Institute, London, UK.
Gloria KayaniDepartment of Statistics, The Thrombosis Research Institute, London, UK.
Keith A A FoxCentre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: Atrial fibrillation (AF) management guidelines advise using risk tools to optimize AF treatment. This study aims to develop a dynamic and clinically applicable digital device to assess stroke and bleeding risk, and to facilitate outcome improvements in AF patients. The device will provide tailored treatment recommendations according to easily attainable individual patient data. Methods and Results: This Universal Clinician Device (UCD) was created using the GARFIELD-AF registry using a split sample approach. The GARFIELD-AF risk tool was adapted with two modifications. First, predictors with ≥1000 missing data points were separated, allowing expected risks estimation. Second, recommendations for modifiable risk factors and associated 2-year outcome estimates were incorporated. Outcomes of interest were all-cause mortality, non-haemorrhagic stroke/systemic embolism (SE), and major bleeding. All patients were randomized to a derivation ( Conclusion: The UCD simultaneously predicts mortality, stroke, and bleeding risk in patients using easily attainable individual clinical data and guideline-based optimized treatment plans. Clinical Trial Registration: URL: http://www.clinicaltrials.gov. Unique identifier for GARFIELD-AF: NCT01090362.

Indexed as

Atrial fibrillationDiabetesManagement guidelinesPersonalized medicineRisk predictionUniversal Clinician Device

Identifiers

PMID36713019
PMCPMC9707904

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Registered trials

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.