Evidence map›Paper›PMID 30349859›Full record

ArticleAnnals of clinical and translational neurology2018

NeurEx: digitalized neurological examination offers a novel high-resolution disability scale.

Peter Kosa, Christopher Barbour, Alison Wichman, Mary Sandford, Mark Greenwood, Bibiana Bielekova

Registry-linked trialAbstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04496830 (Cerebrospinal Fluid-biomarkers-based Diagnostic and Prognostic Models for Multiple Sclerosis), which is not on this map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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.

NCT04496830 completednot on this mapstarted 2020, after this paper: background citation

Cerebrospinal Fluid-biomarkers-based Diagnostic and Prognostic Models for Multiple Sclerosis

TypeobservationalSponsorWashington University School of MedicineRan2020 to 2023Enrolled161ConditionsMultiple Sclerosis
3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Assessing verbal and spatial memory via smartphone.Frontiers in digital health · 2026
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
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  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Digital Twins for Multiple Sclerosis.Frontiers in immunology · 2021
    Review
  17. Article
  18. Article
  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

6 authors.

Peter KosaNeuroimmunological Diseases Section (NDS) National Institute of Allergy and Infectious Diseases (NIAID) National Institutes of Health Bethesda Maryland.
Christopher BarbourNeuroimmunological Diseases Section (NDS) National Institute of Allergy and Infectious Diseases (NIAID) National Institutes of Health Bethesda Maryland.
Alison WichmanNeuroimmunological Diseases Section (NDS) National Institute of Allergy and Infectious Diseases (NIAID) National Institutes of Health Bethesda Maryland.
Mary SandfordNeuroimmunological Diseases Section (NDS) National Institute of Allergy and Infectious Diseases (NIAID) National Institutes of Health Bethesda Maryland.
Mark GreenwoodDepartment of Mathematical Sciences Montana State University Bozeman Montana.
Bibiana BielekovaNeuroimmunological Diseases Section (NDS) National Institute of Allergy and Infectious Diseases (NIAID) National Institutes of Health Bethesda Maryland.

Funding

From therapeutic mechanisms to unraveling the pathophysiology of MSZIAAI001243 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI BIELEKOVA, BIBIANA · 2019 to 2025
$15.8M
6 · The paper itself

Abstract

objectiveTo develop a sensitive neurological disability scale for broad utilization in clinical practice.

methodsWe employed advances of mobile computing to develop an iPad-based App for convenient documentation of the neurological examination into a secure, cloud-linked database. We included features present in four traditional neuroimmunological disability scales and codified their automatic computation. By combining spatial distribution of the neurological deficit with quantitative or semiquantitative rating of its severity we developed a new summary score (called NeurEx; ranging from 0 to 1349 with minimal measurable change of 0.25) and compared its performance with clinician- and App-computed traditional clinical scales.

resultsIn the cross-sectional comparison of 906 neurological examinations, the variance between App-computed and clinician-scored disability scales was comparable to the variance between rating of the identical neurological examination by multiple sclerosis (MS)-trained clinicians. By eliminating rating ambiguity, App-computed scales achieved greater accuracy in measuring disability progression over time (

interpretationNeurEx can be used as a highly sensitive outcome measure in neuroimmunology. The App can be easily modified for use in other areas of neurology and it can bridge private practice practitioners to academic centers in multicenter research studies.

Identifiers

PMID30349859
PMCPMC6186944

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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.