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Record W3175178039 · doi:10.1155/2021/5862444

COVID‐19 Infection in Spinal Muscular Atrophy Associated with Multisystem Inflammatory Syndrome

2021· article· en· W3175178039 on OpenAlexaff
Rafat Mosalli, Amirah Al Matrafi, Mohammed Ghazi, Gamal A. Aboumousatafa, Bosco Paes

Bibliographic record

VenueCase Reports in Pediatrics · 2021
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineSpinal muscular atrophyTocilizumabCoronavirus disease 2019 (COVID-19)HypotoniaNeuromuscular diseasePediatricsGuillain-Barre syndromePopulationDiseaseAtrophyInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The coronavirus disease-2019 (COVID-19) is usually less severe and less prevalent in the pediatric population. Children with preexisting conditions such as neuromuscular impairments and chronic lung disease are more susceptible to COVID-19 and may incur several complications with a poor outcome. We present a case report of a 3-year-old-female with generalized hypotonia and respiratory failure due to spinal muscular atrophy who tested positive for COVID-19 and developed multisystem inflammatory syndrome that was treated with intravenous immunoglobulin and tocilizumab and subsequently died. The report highlights the importance of close surveillance, the use of protective measures during hospital visits, early testing, and diagnosis of COVID-19 in children with neurological disorders.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.299
Teacher spread0.278 · 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 designCase report
Domainnot available
GenreEmpirical

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

Citations1
Published2021
Admission routes1
Has abstractyes

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