Early administration of oral oseltamivir increases the benefits of influenza treatment
Bibliographic record
Abstract
Our objective was to evaluate the benefit of early treatment of influenza illness using oral oseltamivir. This open-label, multicentre international study investigated the relationship between the interval from illness onset to first dose (time-to-treatment) and illness duration in the intent-to-treat infected population using accelerated failure time (AFT) modelling. A total of 1426 patients (12-70 years) presenting within 48 h of the onset of influenza symptoms were treated with oseltamivir 75 mg twice a day for 5 days during the 1999-2000 influenza season; 958 (67%) had laboratory-confirmed influenza virus infection. Earlier intervention was associated with shorter illness duration (P < 0.0001). Initiation of therapy within the first 12 h after fever onset reduced the total median illness duration by 74.6 h (3.1 days; 41%) more than intervention at 48 h. Intermediate interventions reduced the illness proportionately compared with 48 h. In addition, the earlier administration of oseltamivir further reduced the duration of fever, severity of symptoms and the times to return to baseline activity and health scores. Oseltamivir was well tolerated. The most common adverse events were nausea and vomiting, which were transient and generally occurred only with first dosing. When oseltamivir was taken with food, the tolerability was enhanced. The overall discontinuation rate was low (1.8%). In conclusion, the IMPACT study demonstrated that earlier initiation of oral oseltamivir therapy increased its therapeutic effects, which were seen at every time point of intervention and were progressive. Thus, early presentation, diagnosis and treatment of patients with influenza maximized the benefits of oseltamivir therapy.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".