Burden of Seasonal Influenza in Children With Neurodevelopmental Conditions
Bibliographic record
Abstract
BACKGROUND: Studies have identified certain neurologic and neurodevelopmental conditions (NNC) as risk factors for severe influenza infection. The Canadian National Advisory Committee on Immunization does not currently recognize children with NNC as having a high risk of complicated influenza infection unless their condition compromises handling of respiratory secretions. We describe the burden of influenza in hospitalized children with NNC, focusing on those without potential airway compromise. METHODS: Using multi-year surveillance data obtained by the Canadian Immunization Monitoring Program, Active (IMPACT), we examined presenting signs and symptoms, risk factors and outcomes of children hospitalized with seasonal influenza at 12 Canadian pediatric referral centers. Comparisons were made between children with various NNC and other medical conditions, with and without influenza vaccine indications. The analysis is descriptive with selected comparisons made among groups for important indicators of disease severity. RESULTS: We identified 1991 children hospitalized with influenza over 5 seasons: 293 had NNC, 115 of whom did not have airway compromise or another vaccine indication. The latter group presented with seizures more frequently than those with NNC and a vaccine indication (41.7% vs. 26.4%; P = 0.006) and required intensive care unit admission (20.9% vs. 11.8%; P = 0.02) and mechanical ventilation (14.8% vs. 4.5%; P < 0.001) more often than children without NNC but with a vaccine indication. CONCLUSIONS: The burden of influenza infection in children with NNC, even those whose conditions do not obviously compromise respiratory function, is significant. All children with NNC should be recognized as having a high risk of complicated influenza infection and be targeted to receive influenza immunization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".