Influence of age, sex and respiratory viruses on the rates of emergency department visits and hospitalisations with respiratory tract infections, asthma and COPD
Bibliographic record
Abstract
BACKGROUND: The importance of age, sex and respiratory virus prevalence in emergency department (ED) visits and hospitalisations for respiratory tract infections (RTIs), asthma and COPD in a whole population over time is not well established. METHODS: This study retrospectively analysed data for daily ED visits and hospitalisations from 2003 to 2013 in Ontario, Canada and the daily number of virus positive tests. Daily numbers of ED visits and hospitalisations with RTIs, asthma and COPD listed as a primary diagnosis were collected from the Canadian Institute for Health Information. Virus data were obtained from the Respiratory Virus Detection Surveillance System. Multiple linear regression was used to assess the association of individual viruses with the daily rates. RESULTS: There were 4 365 578 ED visits and 321 719 (7.4%) admissions for RTIs, 817 141 ED visits and 260 665 (31.9%) admissions for COPD and 649 666 ED visits and 68 626 (10.6%) admissions for asthma. Respiratory syncytial virus and influenza A were associated with male ED visits, whereas human rhinovirus was associated with female ED visits for RTIs in preschool children. 19.2% of males, but only 7.2% of females were admitted. The correlation between the prevalence of each virus and ED visits and hospitalisations for asthma was weak, irrespective of age group and sex. Influenza A was most strongly associated with COPD ED visits and hospitalisations in males and females. CONCLUSIONS: There are significant age and sex differences in the contribution of respiratory viruses to the number of ED visits and hospitalisations for RTIs, asthma and COPD.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".