Characteristics of children admitted to hospital with acute SARS-CoV-2 infection in Canada in 2020
Bibliographic record
Abstract
BACKGROUND: Risk factors for severe outcomes of SARS-CoV-2 infection are not well established in children. We sought to describe pediatric hospital admissions associated with SARS-CoV-2 infection in Canada and identify risk factors for more severe disease. METHODS: We conducted a national prospective study using the infrastructure of the Canadian Paediatric Surveillance Program (CPSP). Cases involving children who were admitted to hospital with microbiologically confirmed SARS-CoV-2 infection were reported from Apr. 8 to Dec. 31 2020, through weekly online questionnaires distributed to the CPSP network of more than 2800 pediatricians. We categorized hospital admissions as related to COVID-19, incidental, or for social or infection control reasons and determined risk factors for disease severity in hospital. RESULTS: Among 264 hospital admissions involving children with SARS-CoV-2 infection during the 9-month study period, 150 (56.8%) admissions were related to COVID-19 and 100 (37.9%) were incidental infections (admissions for other reasons and found to be positive for SARS-CoV-2 on screening). Infants (37.3%) and adolescents (29.6%) represented most cases. Among hospital admissions related to COVID-19, 52 (34.7%) had critical disease, 42 (28.0%) of whom required any form of respiratory or hemodynamic support, and 59 (39.3%) had at least 1 underlying comorbidity. Children with obesity, chronic neurologic conditions or chronic lung disease other than asthma were more likely to have severe or critical COVID-19. INTERPRETATION: Among children who were admitted to hospital with SARS-CoV-2 infection in Canada during the early COVID-19 pandemic period, incidental SARS-CoV-2 infection was common. In children admitted with acute COVID-19, obesity and neurologic and respiratory comorbidities were associated with more severe disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".