Clinical presentation of Enterovirus D68 in adults with acute respiratory infections consulting in emergency departments in Quebec, Canada
Bibliographic record
Abstract
Objectives: Enterovirus D68 (EV-D68) is mainly studied in children, while data in adults are limited. We described the clinical presentation of EV-D68 in adults, compared with other enterovirus/rhinovirus (EV/RV) infections. Methods: We used clinical and laboratory data from 1143 adults visiting four emergency departments in Quebec, Canada, for acute respiratory infections (February 2022 to March 2023). We analyzed nasopharyngeal swabs using a multiplex polymerase chain reaction; positive EV/RV samples were further tested with EV-D68-specific polymerase chain reaction assays. We calculated the Pandemic Medical Early Warning Score (PMEWS) to assess severity. Results: = 0.02) and tended to have more underlying chronic respiratory diseases (26% vs 20%) and respiratory symptoms (e.g., dyspnea: 84% vs 75%; wheezing: 63% vs 44%; and chest pain: 63% vs 49%), although these differences were not statistically significant. PMEWS, hospitalizations, and median time spent in the emergency department did not differ significantly between the EV-D68 and the other EV/RV group. Conclusions: Respiratory symptoms tended to be more common among participants with EV-D68 than those with other EV/RV, although disease severity was similar. Larger studies are needed to better characterize EV-D68 infections in adults.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".