MétaCan
Menu
Back to cohort
Record W4293588752 · doi:10.30699/mmlj17.5.1.29

COVID-19 vaccination in patients with Multiple Sclerosis: A Practical guide for Neurologists

2022· article· en· W4293588752 on OpenAlexvenueno aff
Seyed Massood Nabavi, Mehrnoosh Mehrabani, Shahedeh Karimi, Ehsan Mohammadianinejad, Mehran Ghafari, Maryam Dastoorpour

Bibliographic record

VenueModern Medical Laboratory Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
Fundersnot available
KeywordsVaccinationMultiple sclerosisCoronavirus disease 2019 (COVID-19)Medicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)DiseaseImmune systemCoronavirusImmunologyIntensive care medicineVirologyInfectious disease (medical specialty)Internal medicineOutbreak

Abstract

fetched live from OpenAlex

Coronavirus disease 2019 (COVID-19) is more common in patients with multiple sclerosis because of receiving immunosuppressive or immunomodulating diseasemodifying therapies (DMTs).On the other hand, some of these drugs may interact on COVID-19 vaccines.In this commentary, first we introduce some available COVID-19 vaccines and then discuss the effect of different DMTs on immune responses after vaccination.We have not found a connection between vaccination and MS relapses, so we suggest that the benefit from the vaccine outweighs any potential risks in these patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.005
Open science0.0020.001
Research integrity0.0100.015
Insufficient payload (model declined to judge)0.0070.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.364
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueModern Medical Laboratory JournalSame topicSARS-CoV-2 and COVID-19 ResearchFrench-language works237,207