483. Disease Severity and Clinical Manifestations of SARS-CoV-2 Infection Among Infants Over the First Year of the Pandemic in Canada
Bibliographic record
Abstract
Abstract Background There is limited data on outcomes of SARS-CoV-2 infection among infants (< 1 year of age). In the absence of any approved vaccines for infants, understanding the risk factors for hospitalization and severe disease from COVID-19 in this age group will help inform clinical management and targeted public health interventions. The objective of this study was to describe the clinical manifestations, disease severity, and risk factors for hospitalization among infants with SARS-CoV-2 infection in Canada. Methods This is a nationwide prospective observational study using the infrastructure of the Canadian Paediatric Surveillance Program. All cases of infants aged < 1 year of age with microbiologically confirmed SARS-CoV-2 infection were reported from April 8th 2020 to May 11th 2021, and classified by disease severity, and primary cause of hospitalization. Logistic regression was performed to identify risk factors for hospitalization and severe disease. Results A total of 393 cases were reported, including 229 (58.3%) non-hospitalized and 164 (41.7%) hospitalized infants. The most common symptoms included fever (63.4%), runny nose (45.0%), cough (35.1%) and decreased oral intake (24.9%). Significant risk factors for hospitalization included younger age and presence of comorbid conditions (excluding prematurity), as shown in the Table. Among hospitalized infants, 108 (65.9%) were admitted because of COVID-19-related illness, and 52 (31.7%) were admitted for reasons other than COVID-19. A total of 31 (7.9%) infants developed severe or critical disease. Risk factors for severe disease included prematurity and younger age (Table). Conclusion We describe one of the largest cohort of infants with SARS-CoV-2 infection. Severe disease in this age group is uncommon, with younger age and prematurity being significant risk factors for severe COVID-19. Disclosures Pierre-Philippe Piché-Renaud, MD, Pfizer Global Medical Grants (Competitive grant program) (Research Grant or Support, Investigator-led project on the impact of COVID-19 on routine childhood immunizations) Olivier Drouin, MDCM MsC MPH, Covis Pharma (Research Grant or Support) Shaun Morris, MD, MPH, DTM&H, FRCPC, FAAP, GSK (Speaker’s Bureau)Pfizer (Advisor or Review Panel member)Pfizer (Grant/Research Support)
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".