Evidence map›Paper›PMID 34651395›Full record

ArticleDiabetes/metabolism research and reviews2022

Similarities and differences between multiple sclerosis and type 1 diabetes.

Valeria Pozzilli, Eleonora Agata Grasso, Valentina Tomassini

Abstract read
In one paragraph

Article in Diabetes/metabolism research and reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. The Integrated Cellular and Molecular Landscape of Autoimmunity.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. Review
  7. 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

3 authors.

Valeria PozzilliDepartment of Neurosciences, Imaging and Clinical Sciences, Institute of Advanced Biomedical Technologies (ITAB), University "G. d'Annunzio" of Chieti-Pescara, Chieti, Italy.
Eleonora Agata GrassoDepartment of Neurosciences, Imaging and Clinical Sciences, Institute of Advanced Biomedical Technologies (ITAB), University "G. d'Annunzio" of Chieti-Pescara, Chieti, Italy.ORCID 0000-0001-7044-8933
Valentina TomassiniDepartment of Neurosciences, Imaging and Clinical Sciences, Institute of Advanced Biomedical Technologies (ITAB), University "G. d'Annunzio" of Chieti-Pescara, Chieti, Italy.ORCID 0000-0002-7368-6280

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple sclerosis (MS) and type 1 diabetes (T1D) are chronic conditions that result from dysfunction of the immune system. Their common root in autoimmunity stimulates interest in the exploration of similarities and differences between the two diseases. Genetic susceptibility is relevant, creating a substrate, on which environmental factors act as a trigger of an aberrant immune response. Despite being both T-cell mediated disorders with a strong involvement of the humoral arm, immunomodulation is a mainstay of MS management, whereas hormone replacement therapy remains the principal approach for T1D. T1D is usually diagnosed in children and adolescents, while MS is typical of young adults. This difference has implications for disease progression and treatment. The SARS-CoV-2 pandemic and its effect on immunity may affect the prevalence of these conditions, as well as their clinical manifestation.

Indexed as

Diabetes Mellitus, Type 1Multiple SclerosisCOVID-19HumansPandemicsautoimmunitycomorbidityCOVID-19multiple sclerosisSARS-CoV-2 infectiontype 1 diabetes

Identifiers

PMID34651395
PMCPMC9285024

What OpenQuestion holds

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Registered trials

None linked

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.