Viral Etiologies of Acute Respiratory Illness in Older Adults and of Congestive Heart Failure and Chronic Obstructive Pulmonary Disease Exacerbations Requiring Hospitalization During 2 Prepandemic Respiratory Seasons
Bibliographic record
Abstract
Background: In adults, the infectious etiologies of acute respiratory illnesses (ARIs) and of exacerbations of cardiopulmonary diseases requiring hospitalization are incompletely understood. Methods: We conducted a prospective surveillance study of older adults hospitalized with acute respiratory illness (ARI) and adults of any age hospitalized with exacerbations of congestive heart failure (CHF) or chronic obstructive pulmonary disease (COPD) at 2 urban hospitals in Atlanta, Georgia, during the 2018-2019 and 2019-2020 respiratory seasons along with contemporaneous healthy controls. All participants had nasopharyngeal and oropharyngeal swabs collected and tested for common viral and bacterial etiologies using a BioFire multiplexed respiratory panel. A subset of patients had paired serological testing for respiratory syncytial virus (RSV), and standard-of-care microbiologic testing results were included when available. Demographics, clinical characteristics, and outcomes were determined through a combination of participant interview and medical record abstraction for hospitalized participants. Results: A total of 1558 participants were enrolled and included in the analysis. Overall, 757 participants (48.6%) were hospitalized for ARI, 490 (31.5%) for CHF exacerbation, and 311 (20.0%) for COPD exacerbation. At least 1 pathogen was detected in 476 (30.6%) participants, most commonly rhinovirus/enterovirus (127/1558 [8.2%]), influenza (119/1558 [7.6%]), and RSV (92/1558 [5.9%]). Although bacterial and fungal infections were uncommon, these were associated with severe clinical outcomes, including duration of hospitalization and mechanical ventilation. Conclusions: Respiratory viruses contributed substantially to hospitalization for ARI and cardiopulmonary exacerbations among our cohort of high-risk adults, underscoring the need for effective therapeutic and preventive interventions in this vulnerable population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".