ArticleFrontiers in neurology2019
A Framework for Estimating the Burden of Chronic Diseases: Design and Application in the Context of Multiple Sclerosis.
Article in Frontiers in neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled 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.
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of studies that estimated the burden of chronic non-communicable rare diseases using disability-adjusted life years.Orphanet journal of rare diseases · 2024Pooled it
- Patient Preferences Towards Plain Language Resources During their Multiple Sclerosis Journey: A Qualitative Interview Study.The patient · 2026Article
- Clinical and epidemiological characteristics of multiple sclerosis in the southern region of the Republic of Azerbaijan.Pakistan journal of medical sciences · 2025Article
- Rising Prevalence of Multiple Sclerosis in Switzerland: Results from the Swiss Multiple Sclerosis Registry.Neuroepidemiology · 2025Article
- Article
- From wearable sensor data to digital biomarker development: ten lessons learned and a framework proposal.NPJ digital medicine · 2024Review
- Escalating to medium- versus high-efficacy disease modifying therapy after low-efficacy treatment in relapsing remitting multiple sclerosis.Brain and behavior · 2024Article
- Blending citizen science with natural language processing and machine learning: Understanding the experience of living with multiple sclerosis.PLOS digital health · 2023Article
- Health system support among patients with ME/CFS in Switzerland.Journal of Taibah University Medical Sciences · 2023Article
- Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis.Frontiers in digital health · 2023Article
- Economic burden of multiple sclerosis in Slovakia - from 2015 to 2020.BMC health services research · 2022Article
- The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing.JMIR medical informatics · 2022Article
- First Insights into Barriers and Facilitators from the Perspective of Persons with Multiple Sclerosis: A Multiple Case Study.International journal of environmental research and public health · 2022Article
- A Data-Driven Simulation of the Exposure Notification Cascade for Digital Contact Tracing of SARS-CoV-2 in Zurich, Switzerland.JAMA network open · 2021Article
- Factors associated with employment and expected work retention among persons with multiple sclerosis: findings of a cross-sectional citizen science study.Journal of neurology · 2020Article
- 60/30: 60% of the Morbidity-Associated Multiple Sclerosis Disease Burden Comes From the 30% of Persons With Higher Impairments.Frontiers in neurology · 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What 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.