Risk factors for severe PCR-positive SARS-CoV-2 infection in hospitalized children: a multicenter cohort study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".