Use of Antiviral Prophylaxis in Influenza Outbreaks in Long Term Care Facilities
Bibliographic record
Abstract
Influenza is a major cause of illness and death in residents of long term care facilities for the elderly, in part because residents' age and underlying illness increase the risk of serious complications, and in part because institutional living increases the risk of influenza outbreaks. The administration of antiviral medications active against influenza to persons exposed to influenza has been shown to protect them effectively from illness, and mass antiviral prophylaxis of residents is an effective means of terminating influenza A outbreaks in long term care facilities. The only antiviral currently licensed in Canada for influenza prophylaxis is amantadine, a medication active against influenza A but not influenza B. The National Advisory Committee on Immunization recommends that amantadine prophylaxis be offered to residents when influenza A outbreaks occur in long term care facilities. However, there remain a number of unanswered questions about how best to use amantadine for controlling influenza A outbreaks in long term care facilities. In addition, two members of a new class of antivirals called neuraminidase inhibitors have recently been licensed in Canada for the treatment of influenza, and are effective in prophylaxis. Issues in the use of amantadine in the control of outbreaks of influenza A in long term care facilities for the elderly are reviewed, and the potential uses of neuraminidase inhibitors in this setting are discussed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".