Characteristics and Outcomes of Young Children Hospitalized With Laboratory-confirmed Influenza or Respiratory Syncytial Virus in Ontario, Canada, 2009–2014
Bibliographic record
Abstract
BACKGROUND: Respiratory illnesses are a major contributor to pediatric hospitalizations, with influenza and respiratory syncytial virus (RSV) causing substantial morbidity and cost each season. We compared the characteristics and outcomes of children 0-59 months of age who were hospitalized with laboratory-confirmed influenza or RSV between 2009 and 2014 in Ontario, Canada. METHODS: We included hospitalized children who were tested for influenza A, influenza B and RSV and were positive for a single virus. We characterized individuals by their demographics and healthcare utilization patterns and compared their hospital outcomes, in-hospital cost and postdischarge healthcare use by virus type and by presence of underlying comorbidities. RESULTS: We identified and analyzed 7659 hospitalizations during which a specimen tested positive for influenza or RSV. Children with RSV were the youngest whereas children with influenza B were the oldest [median ages 6 months (interquartile range: 2-17 months) and 25 months (interquartile range: 10-45 months), respectively]. Complex chronic conditions were more prevalent among children with all influenza (sub)types than RSV (31%-34% versus 20%). In-hospital outcomes were similar by virus type, but in children with comorbidities, postdischarge outcomes varied. We observed no differences in in-hospital cost between viruses or by presence of comorbidities [overall median cost: $4150 Canadian dollars (interquartile range: $3710-$4948)]. CONCLUSIONS: Influenza and RSV account for large numbers of pediatric hospitalizations. RSV and influenza were similar in terms of severity and cost in hospitalized children. Influenza vaccination should be promoted in pregnant women and young children, and a vaccine against RSV would mitigate the high burden of RSV.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".