Burden of noninfluenza respiratory viral infections in adults admitted to hospital: analysis of a multiyear Canadian surveillance cohort from 2 centres
Bibliographic record
Abstract
BACKGROUND: Data on the outcomes of noninfluenza respiratory virus (NIRV) infections among hospitalized adults are lacking. We aimed to study the burden, severity and outcomes of NIRV infections in this population. METHODS: = 2119). We included patients aged ≥ 18 years who developed influenza-like illness or pneumonia and were hospitalized for management. We included patients confirmed positive for ≥ 1 virus by multiplex polymerase chain reaction assays (respiratory syncytial virus [RSV], human rhinovirus/enterovirus (hRV), human coronavirus (hCoV), metapneumovirus, parainfluenza virus, adenovirus, influenza viruses). We compared patient characteristics, clinical severity conventional outcomes (e.g., hospital length-of stay, 30-day mortality) and ordinal outcomes (5 levels: discharged, receiving convalescent care, acute ward or intensive care unit [ICU] care and death) for patients with NIRV infections and those with influenza. RESULTS: = 963). Patients with NIRVs were younger (mean 66.4 [standard deviation 20.4] yr), and more commonly had immunocompromising conditions (30.3%) and delay in diagnosis (median 4.0 [interquartile range (IQR) 2.0-7.0] days). Overall, 14.6% (12.4%-19.5%) of NIRV infections were acquired in hospital. Admission to ICU (18.2%, median 6.0 [IQR 3.0-13.0] d), hospital length-of-stay (median 5.0 [IQR 2.0-10.0] d) and 30-day mortality (8.4%; RSV 9.5%, hRV 6.6%, hCoV 9.2%) and the ordinal outcomes were similar for patients with NIRV infection and those with influenza. Age > 60 years, immunocompromised state and hospital-acquired viral infection were associated with worse outcomes. The estimated median cost per acute care admission was $6000 (IQR $2000-$16 000). INTERPRETATION: The burden of NIRV infection is substantial in adults admitted to hospital and associated outcomes may be as severe as for influenza, suggesting a need to prioritize therapeutics and vaccines for at-risk people.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".