Evidence map›Paper›PMID 31587534›Full record

ReviewJournal of stroke2019

Digital Therapeutics: Emerging New Therapy for Neurologic Deficits after Stroke.

Mi Joo Choi, Hana Kim, Hyun-Wook Nah, Dong-Wha Kang

Abstract readReview
In one paragraph

Review in Journal of stroke, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 3 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

32 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Digital Therapeutics in China: Comprehensive Review.Journal of medical Internet research · 2025
    Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Trial
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  9. Review
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  14. Review
  15. Machine Learning in Clinical Trials: A Primer with Applications to Neurology.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023
    Review
  16. Article
  17. Article
  18. Digital therapeutics in neurology.Journal of neurology · 2022
    Review
  19. Article
  20. Article
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

4 authors.

Mi Joo ChoiSchool of Medical Sciences, University of Manchester, Manchester, UK.
Hana KimDepartment of Neurology, University of Ulsan College of Medicine, Seoul, Korea.
Hyun-Wook NahNunaps Inc., Seoul, Korea.
Dong-Wha KangDepartment of Neurology, University of Ulsan College of Medicine, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital therapeutics is an evidence-based intervention using high-quality software, with the sole purpose of treatment. As many healthcare systems are encountering high demands of quality outcomes, the need for digital therapeutics is gradually increasing in the clinical field. We conducted review of the implications of digital therapeutics in the treatment of neurological deficits for stroke patients. The implications of digital therapeutics have been discussed in four domains: cognition, speech and aphasia, motor, and vision. It was evident that different forms of digital therapeutics such as online platforms, virtual reality trainings, and iPad applications have been investigated in many trials to test its feasibility in clinical use. Although digital therapeutics may deliver high-quality solutions to healthcare services, the medicalization of digital therapeutics is accompanied with many limitations. Clinically validated digital therapeutics should be developed to prove its efficacy in stroke rehabilitation.

Indexed as

AphasiaCognitionDigital therapeuticsHemianopiaHemiplegiaStroke

Identifiers

PMID31587534
PMCPMC6780014

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.