Burden of Hospitalization Associated with Seasonal Influenza in Toronto, Canada, 2011–2016
Bibliographic record
Abstract
Abstract Background As indications for testing for influenza broaden, influenza is increasingly being diagnosed in association with hospitalization in adults. We report data on the burden of illness associated with laboratory confirmed influenza requiring hospitalization (LCI-H) in Toronto, Canada from 2010–2011 to 2015–2016. Methods TIBDN has performed population-based surveillance for LCI-H in adults (≥15years) in Toronto and Peel Region, Canada since 2005. All positive tests for influenza are reported, patients are approached for consent and data collected by chart review and patient/physician interview. Death within 30 days of hospitalization was considered associated with influenza. Population data were obtained from Statistics Canada, with data by underlying condition obtained from literature review and provincial health administrative data. Results Over 6 seasons, 5,591 LCI-H episodes were identified: 1,094 (20%) H1N1, 2,847 (51%) H3N2, 415 (7%) A(not typed), 1A(H3N2 and H1N1) and 1,235 (22%) B. The median age of patients was 71.4 years, with 69.3% of patients over 65 years of age; 3,015 (53.4%) were female, 2,618 (46.8%) had been vaccinated against influenza, and 683 (12.2%) were admitted from nursing homes. Incidence by age, influenza subtype and season is shown in Figures 1 and 2. The average annual incidence in healthy adults was 5 per 100,000, compared with 0.8 per 1,000 in adults with COPD or diabetes, 1.7 per 1,000 in adults with cardiac disease, and >2 per 1,000 in those with underlying kidney disease or immunosuppression. Overall, 12.8% of patients had a significant non-respiratory complication (eg. myocarditis, stroke, C. difficile infection). 720 (12.9%) required ICU admission, and 414 (7.4%) required mechanical ventilation. The median hospital length of stay was 9.58 days (IQR 3-11). None of 226 cases aged <30 years died; the case fatality rate increased from 1.8% in those aged 30–39 to 14.5% in those aged 90+ (Figure 3). Conclusion Despite vaccination programs, influenza is a very common cause of hospitalization and death in our adult population. While surveillance for LCI-H underestimates the overall burden of influenza, it may nonetheless help to appropriately prioritize preventive programs. Disclosures J. Powis, Merck: Grant Investigator, Research grant. GSK: Grant Investigator, Research grant. Roche: Grant Investigator, Research grant. Synthetic Biologicals: Investigator, Research grant. A. Mcgeer, Hoffman La Roche: Investigator, Research grant. GSK: Investigator, Research grant. sanofi pasteur: Investigator, Research grant.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".