Respiratory Syncytial Virus and Other Respiratory Viral Infections in Older Adults With Moderate to Severe Influenza-like Illness
Bibliographic record
Abstract
BACKGROUND: Few studies have prospectively assessed viral etiologies of acute respiratory infections in community-based elderly individuals. We assessed viral respiratory pathogens in individuals ≥65 years with influenza-like illness (ILI). METHODS: Multiplex reverse-transcriptase polymerase chain reaction identified viral pathogens in nasal/throat swabs from 556 episodes of moderate-to-severe ILI, defined as ILI with pneumonia, hospitalization, or maximum daily influenza symptom severity score (ISS) >2. Cases were selected from a randomized trial of an adjuvanted vs nonadjuvanted influenza vaccine conducted in elderly adults from 15 countries. RESULTS: Respiratory syncytial virus (RSV) was detected in 7.4% (41/556) moderate-to-severe ILI episodes in elderly adults. Most (39/41) were single infections. There was a significant association between country and RSV detection (P = .004). RSV prevalence was 7.1% (2/28) in ILI with pneumonia, 12.5% (8/64) in ILI with hospitalization, and 6.7% (32/480) in ILI with maximum ISS > 2. Any virus was detected in 320/556 (57.6%) ILI episodes: influenza A (104/556, 18.7%), rhinovirus/enterovirus (82/556, 14.7%), coronavirus and human metapneumovirus (each 32/556, 5.6%). CONCLUSIONS: This first global study providing data on RSV disease in ≥65 year-olds confirms that RSV is an important respiratory pathogen in the elderly. Preventative measures such as vaccination could decrease severe respiratory illnesses and complications in the elderly.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".