Role of influenza and other respiratory viruses in admissions of adults to Canadian hospitals
Bibliographic record
Abstract
OBJECTIVE: We sought to estimate age-specific hospitalization rates attributed to influenza and other virus for adults. METHODS: Admissions from Canada's national hospitalization database (Canadian Institute of Health Information), from 1994/95 to 1999/2000, were modeled as a function of proxy variables for influenza, respiratory syncytial virus (RSV) and other viral activity, seasonality and trend using a Poisson regression model and stratified by age group. RESULTS: The average annual influenza-attributed hospitalization rate for all adults, 20 years of age or older, over the study period, which included three severe seasons, was an estimated 65/100,000 population (95% CI 63-67). Among persons aged 65 and over, 270-340 admissions per 100,000 population per year were attributed to influenza, while 30-110, 60-90 and 130-350 per 100,000 were attributed to RSV, parainfluenza (PIV) and other respiratory viruses, respectively. Although marked season-to-season variation in age-specific hospitalization rates attributable to influenza was observed in persons 50 years of age and older, increasing risk with age was preserved at all time periods. CONCLUSIONS: Influenza, RSV, PIV and other respiratory viruses were all associated with morbidity requiring hospitalization, while influenza was responsible for peak respiratory admissions. The burden of health care utilization associated with respiratory viruses is appreciable beginning in the sixth decade and increases significantly with age.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".