Evidence map›Paper›PMID 37880288›Full record

ArticleScientific reports2023

Patient-centric assessment of rheumatoid arthritis using a smartwatch and bespoke mobile app in a clinical setting.

Valentin Hamy, Christopher Llop, Christopher W Yee, Luis Garcia-Gancedo, Aoife Maxwell, Wen Hung Chen, Ryan Tomlinson, Priyanka Bobbili, Julien Bendelac, Jessica Landry and 5 more

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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.

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

8 citing papers in PubMed.

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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

15 authors.

Valentin Hamy *Value Evidence and Outcomes, GSK, Brentford, TW8 9GS, UK. valentin.x.hamy@gsk.com.
Christopher Llop *Analysis Group Inc., Boston, USA.
Christopher W YeeAnalysis Group Inc., Boston, USA.
Luis Garcia-GancedoValue Evidence and Outcomes, GSK, Brentford, TW8 9GS, UK.
Aoife MaxwellValue Evidence and Outcomes, GSK, Brentford, TW8 9GS, UK.
Wen Hung ChenValue Evidence and Outcomes, GSK, Philadelphia, USA.
Ryan TomlinsonMedicine Development Leaders, GSK, Philadelphia, USA.
Priyanka BobbiliAnalysis Group Inc., Boston, USA.
Julien BendelacAnalysis Group Inc., Boston, USA.
Jessica LandryAnalysis Group Inc., Boston, USA.
Maral DerSarkissianAnalysis Group Inc., Boston, USA.
Mihran YenikomshianAnalysis Group Inc., Boston, USA.
Elinor A ModyRheumatology Department, Reliant Medical Group, Auburn, USA.
Mei Sheng DuhAnalysis Group Inc., Boston, USA.
Rachel WilliamsValue Evidence and Outcomes, GSK, Philadelphia, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rheumatoid arthritis (RA) is a fluctuating progressive disease requiring frequent symptom assessment for appropriate management. Continuous tracking using digital technologies may provide greater insights of a patient's experience. This prospective study assessed the feasibility, reliability, and clinical utility of using novel digital technologies to remotely monitor participants with RA. Participants with moderate to severe RA and non-RA controls were monitored continuously for 14 days using an iPhone with an integrated bespoke application and an Apple Watch. Participants completed patient-reported outcome measures and objective guided tests designed to assess disease-related impact on physical function. The study was completed by 28 participants with RA, 28 matched controls, and 2 unmatched controls. Completion rates for all assessments were > 97% and were reproducible over time. Several guided tests distinguished between RA and control cohorts (e.g., mean lie-to-stand time [seconds]: RA: 4.77, control: 3.25; P < 0.001). Participants with RA reporting greater stiffness, pain, and fatigue had worse guided test performances (e.g., wrist movement [P < 0.001] and sit-to-stand transition time [P = 0.009]) compared with those reporting lower stiffness, pain, and fatigue. This study demonstrates that digital technologies can be used in a well-controlled, remote clinical setting to assess the daily impact of RA.

Indexed as

Arthritis, RheumatoidMobile ApplicationsFatigueHumansPainPatient-Centered CareProspective StudiesReproducibility of Results

Identifiers

PMID37880288
PMCPMC10600111

What OpenQuestion holds

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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.