Risk factors for hospitalization and severe outcomes of 2009 pandemic H1N1 influenza in Quebec, Canada
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: This case-control study was carried out to estimate risk factors associated with hospitalizations and severe outcomes [intensive care unit (ICU) admission or death] among patients with illness because of laboratory-confirmed 2009 pandemic A/H1N1 virus (pH1N1) during the first wave of pH1N1 activity in the province of Quebec, Canada. PATIENTS/METHODS: We collected epidemiologic information by phone using a standardized questionnaire from patients with laboratory-confirmed pH1N1 illness during the first spring/summer pandemic wave in Quebec, Canada. Risk factors associated with hospitalization were assessed by comparing hospitalized to community cases and for ICU admission or death through comparison with hospitalized cases. RESULTS: Cases (321 hospitalized patients including 47 ICU admissions and 15 deaths) were compared to controls (395 non-hospitalized patients) by using multivariable logistic regression adjusted for gender, age, education, being a health care worker, smoking, seasonal influenza vaccination, delay to consultation, antiviral use before admission, pregnancy, underlying medical conditions, and obesity. Age <5 years, underlying medical conditions (neuromuscular, cardiac, pulmonary, and renal conditions, diabetes, asthma, and other), and delayed consultation were associated with hospitalization. The strongest association with hospitalization was observed for neuromuscular disorders. Antiviral medication before hospital admission protected against severe disease. Association of obesity with hospitalization was not significant after adjustment in multivariable analysis. Among hospitalized patients, age ≥60 years and immune suppression were associated with death. CONCLUSIONS: Previously identified risk factors for seasonal influenza were also associated with increased risk of severe pH1N1 outcomes. The independent role of obesity needs to be further defined.
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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) | 0.002 | 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".