Other Respiratory Viruses Are Important Contributors to Adult Respiratory Hospitalizations and Mortality Even During Peak Weeks of the Influenza Season
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: During peak weeks of seasonal influenza epidemics, severe respiratory infections without laboratory confirmation are typically attributed to influenza. METHODS: In this prospective study, specimens and demographic and clinical data were collected from adults admitted with respiratory symptoms to 4 hospitals during the 8-10 peak weeks of 2 influenza seasons. Specimens were systematically tested for influenza and 13 other respiratory viruses (ORVs) by using the Luminex RVP FAST assay. RESULTS: At least 1 respiratory virus was identified in 46% (21% influenza, 25% noninfluenza; 2% coinfection) of the 286 enrolled patients in 2011-2012 and in 62% (46% influenza, 16% noninfluenza; 3% coinfection) of the 396 enrolled patients in 2012-2013. Among patients aged ≥75 years, twice as many ORVs (32%) as influenza viruses (14%) were detected in 2011-2012. During both seasons, the most frequently detected ORVs were enteroviruses/rhinoviruses (7%), respiratory syncytial virus (6%), human metapneumovirus (5%), coronaviruses (4%), and parainfluenza viruses (2%). Disease severity was similar for influenza and ORVs during both seasons. CONCLUSIONS: Although ORV contribution relative to influenza varies by age and season, during the peak weeks of certain influenza seasons, ORVs may be a more frequent cause of elderly hospitalization than influenza.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it