Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
Multiple Sclerosis l: Introduction01:19

Multiple Sclerosis l: Introduction

Multiple sclerosis is a chronic autoimmune disease of the central nervous system (CNS) that affects the brain, spinal cord, and optic nerves. It is an inflammatory demyelinating disorder and a leading cause of neurological disability in young adults.EpidemiologyMS commonly begins between 20 and 40 years of age and is twice as common in women. Its exact cause remains unclear, but genetic susceptibility contributes, with higher risk in first-degree relatives and identical twins. A greater...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Comparison of Different Methods for the Meta-Analysis of Diagnostic Test Accuracy Studies-A Simulation Study.

Biometrical journal. Biometrische Zeitschrift·2026
Same author

When to Adjust for Multiple Testing: A Unifying Guiding Principle.

Biometrical journal. Biometrische Zeitschrift·2026
Same author

Factors Associated With Disability Improvement and Worsening Independent of Attacks in Patients With AQP4-IgG+ NMOSD and MOGAD: A Multicenter Cohort Study.

Neurology·2026
Same author

Unmet needs in the care of patients with neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein antibody associated disease: insights from Germany.

Neurological research and practice·2026
Same author

Burnout and Work-Life Balance: A Longitudinal Study Into the Transition From Medical School to Postgraduate Training.

Deutsches Arzteblatt international·2026
Same author

Agreement of minimally invasive pulse wave analysis with pulmonary artery and transpulmonary thermodilution cardiac output measurements in perioperative and intensive care medicine: a systematic review and meta-analysis.

British journal of anaesthesia·2026

Related Experiment Video

Updated: May 11, 2026

The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool
11:35

The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool

Published on: June 30, 2014

Insights Into Disability and Disability Progression in People With Multiple Sclerosis Using Large-Scale Healthcare

Onur Dereli1, Jochen Behringer2, Achim Berthele1

  • 1Department of Neurology, TUM School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.

European Journal of Neurology
|March 31, 2025
PubMed
Summary
This summary is machine-generated.

Healthcare data reveals factors influencing multiple sclerosis (MS) disability progression. Certain conditions, like gynecological disorders and asthma, were unexpectedly linked to lower nursing care needs in people with MS (PwMS).

Keywords:
disability progressionhealthcare datamachine learningmultiple sclerosisprediction

More Related Videos

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Measuring Progressive Neurological Disability in a Mouse Model of Multiple Sclerosis
08:11

Measuring Progressive Neurological Disability in a Mouse Model of Multiple Sclerosis

Published on: November 14, 2016

Related Experiment Videos

Last Updated: May 11, 2026

The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool
11:35

The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool

Published on: June 30, 2014

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Measuring Progressive Neurological Disability in a Mouse Model of Multiple Sclerosis
08:11

Measuring Progressive Neurological Disability in a Mouse Model of Multiple Sclerosis

Published on: November 14, 2016

Area of Science:

  • Healthcare research
  • Epidemiology
  • Data science

Background:

  • Identifying predictors of disability progression is crucial for managing multiple sclerosis (MS).
  • This study explores disability levels and progression factors in people with MS (PwMS) using healthcare data.
  • The research addresses the challenge of assessing disability without detailed clinical information.

Purpose of the Study:

  • To explore disability levels in people with MS (PwMS) using healthcare utilization data.
  • To identify informative healthcare-related factors associated with disability progression in PwMS.
  • To assess the feasibility of using large healthcare datasets for disease progression studies.

Main Methods:

  • A case-control/cohort study utilized data from Bavaria's largest health insurance organization.
  • Included records on assistive devices, nursing care, sick leaves, rehabilitation, drug therapies, and diagnoses for MS, Crohn's disease (CD), rheumatoid arthritis (RA), and controls (CTR).
  • Generalized linear models and a gradient-boosting algorithm were employed to analyze healthcare service utilization and identify disability progression predictors.

Main Results:

  • People with MS (PwMS) showed higher healthcare utilization than other groups, even at young ages.
  • Beyond expected factors (age, smoking, diabetes, psychiatric disorders), specific gynecological disorders, upper tract infections, asthma, and thyroiditis were associated with lower likelihood of needing higher nursing care.
  • The findings highlight an unmet need for improved management strategies for young adults with MS.

Conclusions:

  • Healthcare data provides an objective method for assessing disability and identifying progression factors in PwMS.
  • The approach is applicable to large cohorts lacking detailed clinical data and adaptable to various diseases and healthcare systems.
  • Early and high healthcare resource utilization in young adults with MS indicates a need for enhanced treatment and management strategies.