Risk factors for severe PCR-positive SARS-CoV-2 infection in hospitalized children: a multicenter cohort study
Notice bibliographique
Résumé
Abstract Importance Children are less likely than adults to have severe outcomes from SARS-CoV-2 infection and the corresponding risk factors are not well established. Objective To identify risk factors for severe disease in symptomatic children hospitalized for PCR-positive SARS-CoV-2 infection. Design Cohort study, enrollment from February 1, 2020 until May 31, 2021 Setting 15 children’s hospitals in Canada, Iran, and Costa Rica Participants Patients <18 years of age hospitalized with symptomatic SARS-CoV-2 infection, including PCR-positive multisystem inflammatory syndrome in children (MIS-C) Exposures Variables assessed for their association with disease severity included patient demographics, presence of comorbidities, clinical manifestations, laboratory parameters and chest imaging findings. Main Outcomes and Measures The primary outcome was severe disease defined as a WHO COVID-19 clinical progression scale of ≥6, i.e., requirement of non-invasive ventilation, high flow nasal cannula, mechanical ventilation, vasopressors, or death. Multivariable logistic regression was used to evaluate factors associated with severe disease. Results We identified 403 hospitalizations. Median age was 3.78 years (IQR 0.53-10.77). At least one comorbidity was present in 46.4% (187/403) and multiple comorbidities in 18.6% (75/403). Severe disease occurred in 33.8% (102/403). In multivariable analyses, presence of multiple comorbidities (adjusted odds ratio 2.24, 95% confidence interval 1.04-4.81), obesity (2.87, 1.19-6.93), neurological disorder (3.22, 1.37-7.56), anemia, and/or hemoglobinopathy (5.88, 1.30-26.46), shortness of breath (4.37, 2.08-9.16), bacterial and/or viral coinfections (2.26, 1.08-4.73), chest imaging compatible with COVID-19 (2.99, 1.51-5.92), neutrophilia (2.60, 1.35-5.02), and MIS-C diagnosis (3.86, 1.56-9.51) were independent risk factors for severity. Comorbidities, especially obesity (40.9% vs 3.9%, p<0.001), were more frequently present in adolescents ≥12 years of age. Neurological disorder (3.16, 1.19-8.43) in children <12 years of age and obesity (3.21, 1.15-8.93) in adolescents were the specific comorbidities associated with disease severity in age-stratified adjusted analyses. Sensitivity analyses excluding the 81 cases with MIS-C did not substantially change the identified risk factors. Conclusions and Relevance Pediatric risk factors for severe SARS-CoV-2 infection vary according to age and can potentially guide vaccination programs and treatment approaches in children. Key points Question What are the risk factors for severe disease in children hospitalized for PCR-positive SARS-CoV-2 infection? Findings In this multinational cohort study of 403 children, multiple comorbidities, obesity, neurological disorder, anemia, and/or hemoglobinopathy, shortness of breath, bacterial and/or viral coinfections, chest imaging compatible with COVID-19, neutrophilia, and MIS-C diagnosis were independent risk factors for severity. The risk profile and presence of comorbidities differed between pediatric age groups, but age itself was not associated with severe outcomes. Meaning These results can inform targeted treatment approaches and vaccine programs that focus on patient groups with the highest risk of severe outcomes.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».