Severity and Outcome Associated With Human Coronavirus OC43 Infections Among Children
Bibliographic record
Abstract
BACKGROUND: Human coronaviruses are known causes of the common cold. Subtype OC43 (HCoV-OC43) is the more prevalent human coronavirus in several parts of the world. Recent studies have suggested these viruses can cause severe lower respiratory tract illnesses in children. OBJECTIVE: We sought to determine the epidemiology, clinical characteristics, outcomes and severity of illness associated with HCoV-OC43 infections in a pediatric population. METHODS: We retrospectively identified patients with positive HCoV-OC43 respiratory specimens between December 2009 and December 2010 in a pediatric hospital in Montreal. Each case was compared with 2 controls (tested negative for HCoV-OC43). Clinical characteristics, underlying conditions, outcomes and disease severity were reviewed for both groups. Risk factors and independent predictors of disease severity were also assessed. RESULTS: During the study period, 68 patients were identified as infected with HCoV-OC43 (1.8% of specimens tested, 4.2% of all respiratory viruses identified by reverse transcription polymerase chain reaction). The majority (77%) occurred in November 2010. Chief symptoms of HCoV-OC43 infection were fever (in 78% of cases), cough (67%) and upper respiratory tract infection symptoms (57%). HCoV-OC43 infection was not more frequent in children with preexisting conditions. Coinfection with other respiratory viruses was associated with lower respiratory tract infections in HCoV-OC43-infected cases, but did not lead to increased rates of hospitalization, admission to intensive care unit or death. CONCLUSIONS: In our population, HCoV-OC43 infections generally caused upper respiratory tract infection, but can be associated with lower respiratory tract infection especially in those coinfected with other respiratory viruses.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".