Relative Severity of Common Human Coronaviruses and Influenza in Patients Hospitalized With Acute Respiratory Infection: Results From 8-Year Hospital-Based Surveillance in Quebec, Canada
Bibliographic record
Abstract
BACKGROUND: Few data exist concerning the role of common human coronaviruses (HCoVs) in patients hospitalized for acute respiratory infection (ARI) and the severity of these infections compared with influenza. METHODS: Prospective data on the viral etiology of ARI hospitalizations during the peaks of 8 influenza seasons (from 2011-2012 to 2018-2019) in Quebec, Canada, were used to compare patients with HCoV and those with influenza infections; generalized estimation equations models were used for multivariate analyses. RESULTS: We identified 340 HCoV infections, which affected 11.6% of children (n = 136) and 5.2% of adults (n = 204) hospitalized with ARI. The majority of children (75%) with HCoV infections were also coinfected with other respiratory viruses, compared with 24% of the adults (P < .001). No deaths were recorded in children; 5.8% of adults with HCoV monoinfection died, compared with 4.2% of those with influenza monoinfection (P = .23). The risk of pneumonia was nonsignificantly lower in children with HCoV than in those with influenza, but these risks were similarly high in adults. Markers of severity (length of stay, intensive care unit admissions, and case-fatality ratio) were comparable between these infections in multivariate analyses, in both children and adults. CONCLUSIONS: In children and adults hospitalized with ARI, HCoV infections were less frequent than influenza infections, but were as severe as influenza monoinfections.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| 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".