Antiviral Therapy and Outcomes of Influenza Requiring Hospitalization in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: We conducted a prospective cohort study to assess the impact of antiviral therapy on outcomes of patients hospitalized with influenza in southern Ontario, Canada. METHODS: Patients admitted to Toronto Invasive Bacterial Diseases Network hospitals with laboratory-confirmed influenza from 1 January 2005 through 31 May 2006 were enrolled in the study. Demographic and medical data were collected by patient and physician interview and chart review. The main outcome evaluated was death within 15 days after symptom onset. RESULTS: Data were available for 512 of 541 eligible patients. There were 185 children (<15 years of age), none of whom died and none of whom were treated with antiviral drugs. The median age of the 327 adults was 77 years (range, 15-98 years), 166 (51%) were male, 245 (75%) had a chronic underlying illness, and 216 (71%) had been vaccinated against influenza. Of the 327 adult patients, 184 (59%) presented to the emergency department within 48 h after symptom onset, 52 (16%) required intensive care unit admission, and 27 (8.3%) died within 15 days after symptom onset. Most patients (292 patients; 89%) received antibacterial therapy; 106 (32%) were prescribed antiviral drugs. Treatment with antiviral drugs active against influenza was associated with a significant reduction in mortality (odds ratio, 0.21; 95% confidence interval, 0.06-0.80; n=100, 260). There was no apparent impact of antiviral therapy on length of stay in survivors. CONCLUSIONS: There is a significant burden of illness attributable to influenza in this highly vaccinated population. Treatment with antiviral drugs was associated with a significant reduction in mortality.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".