Evidence map›Paper›PMID 39406154›Full record

ArticleMultiple sclerosis and related disorders2024

Impact of insurance status on MRI phenotypes in MS.

Melissa Lynne Martin, Timothy Robert-Fitzgerald, Matthew K Schindler, Christopher Perrone, Guy Schultz, Selah Lynch, Nebojsa Mirkovic, Sunil Thomas, Ameena Elahi, Donovan Reid and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Multiple sclerosis and related disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

22 authors.

Melissa Lynne MartinDepartment of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address: martin30@pennmedicine.upenn.edu.
Timothy Robert-FitzgeraldPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Matthew K SchindlerDepartment of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Christopher PerroneDepartment of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Guy SchultzData Analytics Center, University of Pennsylvania, Philadelphia, PA 19104, USA.
Selah LynchClinical Research Informatics Core, Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Nebojsa MirkovicClinical Research Informatics Core, Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Sunil ThomasClinical Research Informatics Core, Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Ameena ElahiDepartment of Information Services, University of Pennsylvania, Philadelphia, PA 19104, USA.
Donovan ReidDepartment of Information Services, University of Pennsylvania, Philadelphia, PA 19104, USA.
Tyler M MooreDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
Erica B BallerDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA.
Theodore D SatterthwaiteDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA.
Matthew CieslakDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA.
Sydney CovitzDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA.
Azeez AdebimpeDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA.
Abigail ManningPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Clyde E MarkowitzDepartment of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA.
John A DetreDepartment of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Amit Bar-OrDepartment of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Mihir KakaraDepartment of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Russell T ShinoharaDepartment of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA.

Funding

Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
Harmonization of Multi-Site Neuroimaging Data from Complex Study DesignsR01MH123550 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2020 to 2025
$4.0M
Advanced Statistical Analytics of MRI in MSR01NS112274 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2020 to 2024
$2.8M
Depression as a disease of network disruption: learning from multiple sclerosisK23MH133118 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Erica Berlin Baller · 2023 to 2026
$780k
NIMH NIH HHS K23 MH133118NIMH NIH HHS R01 MH112847NIMH NIH HHS R01 MH123550NINDS NIH HHS R01 NS112274
6 · The paper itself

Abstract

backgroundHealth insurance in the United States varies in coverage of essential diagnostic tests, therapies, and specialists. Health disparities between privately and publicly insured patients with MS have not been comprehensively assessed. The objective of this study is to evaluate the impact of public versus private insurance on longitudinal brain outcomes in MS.

methodsLesional, thalamic, and gray and white matter volumes were extracted from longitudinal MRI of 710 MS patients. Baseline volumes and atrophy rates of lesional, thalamic, and gray and white matter volumes were compared across insurance groups.

resultsAfter image quality assessment, 376 (284 private / 92 public), 638 (499 / 139), and 331 (250 / 81), patients were in MS lesion, thalamic, gray and white matter analyses respectively. Baseline lesion volume was higher for publicly insured patients but increased at a slightly higher rate in those privately insured (p = 0.01). Baseline gray matter measurements were lower for patients with public insurance, but thalamic (p < 0.01) and gray matter (p < 0.01) atrophy rates were slightly higher in the private insurance group.

conclusionInsurance type was associated with lesion, thalamic, and gray matter volumes. The results suggest that patients with public insurance may present with more advanced disease.

Indexed as

Insurance CoverageInsurance, HealthMagnetic Resonance ImagingMultiple SclerosisAdultAtrophyBrainFemaleGray MatterHumansLongitudinal StudiesMaleMiddle AgedPhenotypeUnited StatesWhite MatterHealth disparitiesMagnetic resonance imagingMultiple sclerosisRetrospective study

Identifiers

PMID39406154
PMCPMC11649446

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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.