481. Trends in SARS-CoV-2-related Pediatric Hospitalizations in the Canadian Nosocomial Infection Surveillance Program, March 2020 to December 2022
Bibliographic record
Abstract
Abstract Background National surveillance can provide insights into trends in pediatric SARS-CoV-2-related hospitalizations during the pandemic and healthcare-associated infections.Figure:Proportion of all pediatric hospitalizations by age group and wave Methods From March 1, 2020, to December 31, 2022, the Canadian Nosocomial Infection Surveillance Program collected patient-level data on pediatric patients (under age 18 years) hospitalized with laboratory-confirmed SARS-CoV-2 from 9 pediatric and 25 mixed adult-pediatric hospitals. Pediatric COVID-19 vaccines became available for 12-17 years in May 2021 and for 5-11 years in November 2021. Results Of 4,878 pediatric patients, most (80.3%) were hospitalized with SARS-CoV-2 infection during the Omicron-dominant period (since Jan 2022); a higher proportion involved patients under five years of age (58.5% vs 46.9%, p < 0.001). Most hospitalizations pre-Omicron involved children not vaccinated against COVID-19 (92%) versus 70% during Omicron (p < 0.001). However, a lower proportion required intensive care during Omicron (15% vs 20%, p < 0.001). There was no difference in pre-existing comorbidities or mortality between periods. Overall, there were 257 healthcare-associated COVID-19 infections (HA-COVID) reported (5.4%); 89% occurred during Omicron. While there was no difference in median ages of patients with HA-COVID and community-associated COVID-19 infections (CA-COVID), 62% of patients with HA-COVID had a pre-existing comorbidity compared to 44% with CA-COVID (p < 0.001), and 24% remained in hospital at 30 days after HA-COVID, compared to 2.2% with CA-COVID (p < 0.001). Nearly 50% of patients with HA-COVID had received at least one vaccine dose, compared to 25% with CA-COVID. Conclusion During the Omicron-dominant period, a higher proportion of admitted patients with SARS-CoV-2 infection were under five years, but a lower proportion were unvaccinated and a lower proportion required intensive care and mortality was comparable between both periods. Only 5.4% of pediatric COVID-related hospitalizations were HAI, with most during Omicron. Patients with HAI were more likely to have a pre-existing comorbidity and increased hospital stay, potentially related to their underlying conditions. Disclosures All Authors: No reported disclosures
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".