ArticleTrials2026
Recruitment of the multiple sclerosis cohort within the European Mobilise-D clinical validation study-lessons learnt, baseline demographics and clinical characteristics.
Article in Trials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Validation of an Algorithmic Pipeline for Wrist-Worn Devices to Estimate Walking Speed in People with Multiple Long-Term Conditions.Sensors (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
26 authors.
Funding
Abstract
backgroundMultiple sclerosis (MS) is a common cause of disability in working age adults. Current clinical assessments are inadequate at disability assessment or predicting clinically relevant outcomes. Loss of mobility is an important functional disability to people with MS. Mobilise-D aims to develop, validate, and implement a digital mobility solution which measures unsupervised mobility performance across several chronic conditions, including MS, using a single wearable device.
methodsSix hundred two adults with MS, an Expanded Disability Status Scale (EDSS) score of 3.0-6.5, documented disability worsening over the previous 2 years and a 30-day freedom from relapses, were recruited across four European centres.
resultsOf 1416 invited, 602 participants (42%) were recruited. Primary recruitment sources were clinicians (42%) and local registries (42%). Among 616 who declined screening, the main reasons were a lack of interest (44%), the time commitment (25%) or the travel involved (13%). Participants had a mean age of 52 years; 64% were female, with a median EDSS score of 5.0. Of those, 56% had relapsing-remitting MS, 33% secondary progressive MS and 10% primary progressive MS. Falls occurred in 58% of participants in the 12 months prior to recruitment. Of those recruited, 556 (93%) participants had valid mobility data recorded.
conclusionsThe longitudinal collection of clinical and unsupervised mobility assessments will provide a comprehensive dataset, allowing for the determination of digital mobility assessments' construct validity, predictive capacity, responsiveness, and clinical meaningfulness. Novel insights into real-world mobility that describe both walking activity and gait outcomes will be gained.
trial registrationThe study was registered at the ISRCTN registry on 12/10/2020, titled "Clinical validation of a mobility monitor to measure and predict health outcomes" (ISRCTN Number: 12051706).
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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 Socratic graph.