Impact of respiratory viral infections on mortality and critical illness among hospitalized patients with chronic obstructive pulmonary disease
Bibliographic record
Abstract
BACKGROUND: Seasonal respiratory viral infections are associated with exacerbations and morbidity among patients with COPD. The real-world clinical outcomes associated with seasonal viral infections are less well established among hospitalized patients. RESEARCH QUESTION: To estimate the association between seasonal respiratory viral infections, 30-day mortality, and intensive care unit (ICU) admission among hospitalized COPD patients. STUDY DESIGN AND METHODS: We conducted an analysis of a national prospective multicenter cohort of COPD patients hospitalized with acute respiratory illness during winter seasons (2011-2015) in Canada. Nasopharyngeal swabs were performed on all patients at the onset of hospital admission for diagnosis of viral infection. Primary outcomes were 30-day mortality and ICU admissions. Secondary outcomes included invasive/non-invasive ventilation use. RESULTS: Among 3931 hospitalized patients with COPD, 28.5% (1122/3931) were diagnosed with seasonal respiratory viral infection. Viral infection was associated with increased admission to ICU (OR 1.5, 95% CI 1.2-1.9) and need for mechanical ventilation (OR 1.9, 95% CI 1.4-2.5), but was not associated with mortality (OR 1.1, 95% CI 0.8-1.4). Patients with respiratory syncytial virus (RSV) were equally likely to require ICU admission (OR 1.09, 95% CI 0.67-1.78), and more likely to need non-invasive ventilation (OR 3.1; 95% CI 1.8-5.1) compared to patients with influenza. INTERPRETATION: Our results suggest COPD patients requiring hospitalization for respiratory symptoms should routinely receive viral testing at admission, especially for RSV and influenza, to inform prognosis, clinical management, and infection control practices during winter seasons. Patients with COPD will be an important target population for newly developed RSV therapeutics. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT01517191.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".