Evidence map›Paper›PMID 34073464›Full record

ReviewJournal of clinical medicine2021

Digital Technology in Clinical Trials for Multiple Sclerosis: Systematic Review.

Marcello De Angelis, Luigi Lavorgna, Antonio Carotenuto, Martina Petruzzo, Roberta Lanzillo, Vincenzo Brescia Morra, Marcello Moccia

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
–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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Review
  6. Review
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Technologies in Home-Based Digital Rehabilitation: Scoping Review.JMIR rehabilitation and assistive technologies · 2023
    Article
  16. Article
  17. Decentralised clinical trials in multiple sclerosis research.Multiple sclerosis (Houndmills, Basingstoke, England) · 2023
    Review
  18. Review
  19. Review
  20. 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

7 authors.

Marcello De AngelisMultiple Sclerosis Clinical Care and Research Centre, Department of Neuroscience, Reproductive Science and Odontostomatology, Federico II University of Naples, 80138 Naples, Italy.
Luigi LavorgnaDepartment of Medical, Surgical, Neurological, Metabolic and Aging Sciences, University of Campania "Luigi Vanvitelli", 81100 Naples, Italy.ORCID 0000-0003-4625-4236
Antonio CarotenutoMultiple Sclerosis Clinical Care and Research Centre, Department of Neuroscience, Reproductive Science and Odontostomatology, Federico II University of Naples, 80138 Naples, Italy.ORCID 0000-0002-1574-9693
Martina PetruzzoMultiple Sclerosis Clinical Care and Research Centre, Department of Neuroscience, Reproductive Science and Odontostomatology, Federico II University of Naples, 80138 Naples, Italy.
Roberta LanzilloMultiple Sclerosis Clinical Care and Research Centre, Department of Neuroscience, Reproductive Science and Odontostomatology, Federico II University of Naples, 80138 Naples, Italy.ORCID 0000-0001-6388-8180
Vincenzo Brescia MorraMultiple Sclerosis Clinical Care and Research Centre, Department of Neuroscience, Reproductive Science and Odontostomatology, Federico II University of Naples, 80138 Naples, Italy.
Marcello MocciaMultiple Sclerosis Clinical Care and Research Centre, Department of Neuroscience, Reproductive Science and Odontostomatology, Federico II University of Naples, 80138 Naples, Italy.ORCID 0000-0003-2613-3090

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical trials in multiple sclerosis (MS) have been including digital technology tools to overcome limitations in treatment delivery and disease monitoring. In March 2020, we conducted a systematic search on pubmed.gov and clinicaltrials.gov databases (with no restrictions) to identify all relevant published and unpublished clinical trials, in English language, including MS patients, in which digital technology was applied. We used "multiple sclerosis" and "clinical trial" as the main search words, and "app", "digital", "electronic", "internet" and "mobile" as additional search words, separately. Digital technology is part of clinical trial interventions to deliver psychotherapy and motor rehabilitation, with exergames, e-training, and robot-assisted exercises. Digital technology has been used to standardise previously existing outcome measures, with automatic acquisitions, reduced inconsistencies, and improved detection of symptoms (e.g., electronic recording of motor performance). Other clinical trials have been using digital technology for monitoring symptoms that would be otherwise difficult to detect (e.g., fatigue, balance), for measuring treatment adherence and side effects, and for self-assessment purposes. Collection of outcome measures is progressively shifting from paper-based on site, to internet-based on site, and, in the future, to internet-based at home, with the detection of clinical and treatment features that would have remained otherwise invisible. Similarly, remote interventions provide new possibilities of motor and cognitive rehabilitation.

Indexed as

clinical trialdigital technologymultiple sclerosisoutcome measures

Identifiers

PMID34073464
PMCPMC8199078

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.