Hospitalizations and Deaths Due to Respiratory Illnesses During Influenza Seasons: A Comparison of Community Residents, Senior Housing Residents, and Nursing Home Residents
Bibliographic record
Abstract
BACKGROUND: Although research indicates that influenza is a major cause of morbidity and mortality among older adults, few studies have tried to identify which seniors are particularly at risk of experiencing complications of influenza. The purpose of this study was to compare hospitalizations and deaths due to respiratory illnesses during influenza seasons among seniors (aged 65+) living in the community, senior residences (apartments reserved for seniors), and nursing homes. METHODS: Using administrative data, all hospital admissions and deaths due to respiratory illnesses (pneumonia and influenza, chronic lung disease, and acute respiratory diseases) were identified for all individuals aged 65 and older living in Winnipeg, Canada (approximately 88,000 individuals) during four influenza seasons (1995-1996 to 1998-1999). RESULTS: Hospitalization and death rates for respiratory illnesses increased significantly during influenza seasons, compared to fall periods (e.g., 42.7 vs 25.2 hospitalizations per 1000 population aged 80 and older). Moreover, hospitalization rates for pneumonia and influenza, chronic lung disease, and acute respiratory diseases were higher among individuals living in senior residences (42.5 per 1000 for all respiratory illnesses combined) than their counterparts living in the community (22.8 per 1000). Furthermore, deaths due to pneumonia and influenza and chronic lung disease were higher among senior housing residents (4.2 per 1000) than community residents (2.6 per 1000) and were particularly high among nursing home residents (52.1 per 1000). CONCLUSIONS: Individuals living in seniors residences are at increased risk of being hospitalized for and dying of respiratory illnesses during influenza seasons. Given that influenza vaccination is currently the best method to reduce influenza-associated illnesses among seniors, this suggests that influenza vaccination strategies should be targeted at this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".