ReviewDer Nervenarzt2019
[Enhancing monitoring of disease progression-remote sensoring in multiple sclerosis].
Review in Der Nervenarzt, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- [Orthopaedics of the future : AI meets motion analysis: opportunities and risks].Orthopadie (Heidelberg, Germany) · 2025Review
- Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis.Frontiers in digital health · 2023Article
- Digital Biomarkers in Multiple Sclerosis.Brain sciences · 2021Review
- Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data.Brain sciences · 2021Article
- Electronic Health Interventions in the Case of Multiple Sclerosis: From Theory to Practice.Brain sciences · 2021Review
- A Digital Patient Portal for Patients With Multiple Sclerosis.Frontiers in neurology · 2020Article
- Should We Use Clinical Tools to Identify Disease Progression?Frontiers in neurology · 2020Review
- The Dresden Protocol for Multidimensional Walking Assessment (DMWA) in Clinical Practice.Frontiers in neuroscience · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs a result of innovations in the digitalization of healthcare new technologies, such as remote sensoring are gaining in importance for the collection of real-life data in addition to the regular medical examination. This enables a closer view into the daily lives of patients with multiple sclerosis and a more detailed monitoring of disease progression.
objectiveThis article gives a summary of sensor-based measurement technologies in the field of multiple sclerosis
resultsA wide variety of sensor-based measurement technologies are already available, which largely focus on gait analysis and mobility. Furthermore, there are many innovative approaches for a sensor-based collation of the multifocal symptoms of multiple sclerosis, for example technologies focus on the area of stress surveillance, the autonomic nervous system, GPS tracking and sleep monitoring. DISCUSSION: Despite the existence of many already available technologies, the aim is now to find a practical way to integrate them into the daily routine of patient monitoring, which includes standardized data collection, evaluation and interpretation. Only at this point a perspective benefit for treating physicians and patients can be achieved.
Indexed as
Identifiers
31641794What OpenQuestion holds
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 OpenQuestion graph.