Evidence map›Paper›PMID 40460337›Full record

ReviewNeurology2025

Remote Monitoring of Amyotrophic Lateral Sclerosis Using Digital Health Technologies: Shifting Toward Digitalized Care and Research?

Jordi W J van Unnik, Leslie Ing, Miguel Oliveira Santos, Christopher J McDermott, Mamede de Carvalho, Ruben P A van Eijk

Abstract readReview
In one paragraph

Review in Neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

6 authors.

Jordi W J van UnnikDepartment of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.
Leslie IngSheffield Institute for Translational Neuroscience, University of Sheffield, United Kingdom.
Miguel Oliveira SantosInstitute of Physiology, Faculty of Medicine, University of Lisbon, Portugal.ORCID 0000-0002-8290-0410
Christopher J McDermottSheffield Institute for Translational Neuroscience, University of Sheffield, United Kingdom.ORCID 0000-0002-1269-9053
Mamede de CarvalhoInstitute of Physiology, Faculty of Medicine, University of Lisbon, Portugal.ORCID 0000-0001-7556-0158
Ruben P A van EijkDepartment of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current care and research pathways for amyotrophic lateral sclerosis (ALS) primarily rely on regularly scheduled visits to specialized centers. These visits provide intermittent clinical information to health care professionals and require patients to travel to the clinic. Digital health technologies enable continuous data collection directly from the patient's home, bringing new opportunities for personalized, timely care and a refined assessment of disease severity in clinical trials. In this review, we summarize the state of the art in digital health technologies for remote monitoring of patients with ALS, ranging from televisits through videoconferencing to sensor-based wearable devices. We explore how these technologies can benefit clinical care and advance treatment development. Despite significant progress, real-world adoption of these technologies remains limited. An overview is provided of the key barriers hindering their widespread implementation and the opportunities to advance the field. Significantly, there is an urgent need for harmonization across stakeholders through consensus guidelines and consortia. These efforts are essential to accelerate progress and harness the full potential of digital health technologies to better meet the needs of patients.

Indexed as

Amyotrophic Lateral SclerosisBiomedical TechnologyTelemedicineDigital HealthDigital TechnologyHumansMonitoring, PhysiologicVideoconferencingWearable Electronic Devices

Identifiers

PMID40460337
PMCPMC12187388

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.