MétaCan
Menu
Back to cohort
Record W4397002149 · doi:10.3390/v16050801

The Effect of Age and Comorbidities: Children vs. Adults in Their Response to SARS-CoV-2 Infection

2024· article· en· W4397002149 on OpenAlexaff
Girlande Mentor, Daniel S. Farrar, Costanza Di Chiara, Mi‐Suk Kang Dufour, Silvie Valois, Suzanne Taillefer, Olivier Drouin, Christian Renaud, Fatima Kakkar

Bibliographic record

VenueViruses · 2024
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsHospital for Sick ChildrenUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineYoung adultProspective cohort studyImmunosuppressionOdds ratioImmunologyCohortCohort studySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Internal medicineAntibodyCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

While children have experienced less severe coronavirus disease (COVID-19) after SARS-CoV-2 infection than adults, the cause of this remains unclear. The objective of this study was to describe the humoral immune response to COVID-19 in child vs. adult household contacts, and to identify predictors of the response over time. In this prospective cohort study, children with a positive SARS-CoV-2 polymerase chain reaction (PCR) test (index case) were recruited along with their adult household contacts. Serum IgG antibodies against SARS-CoV-2 S1/S2 spike proteins were compared between children and adults at 6 and 12 months after infection. A total of 91 participants (37 adults and 54 children) from 36 families were enrolled. Overall, 78 (85.7%) participants were seropositive for anti-S1/S2 IgG antibody at 6 months following infection; this was higher in children than in adults (92.6% vs. 75.7%) (p = 0.05). Significant predictors of a lack of SARS-CoV-2 seropositivity were age ≥ 25 vs. < 12 years (odds ratio [OR] = 0.23, p = 0.04), presence of comorbidities (vs. none, adjusted OR = 0.23, p = 0.03), and immunosuppression (vs. immunocompetent, adjusted OR = 0.17, p = 0.02).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.354
Teacher spread0.323 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueVirusesSame topicSARS-CoV-2 and COVID-19 ResearchFrench-language works237,207