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Record W2129915170

The treatment of influenza with antiviral drugs.

2003· article· en· W2129915170 on OpenAlexaff
Grant Stiver

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRimantadineZanamivirAmantadineOseltamivirMedicineVaccinationNeuraminidaseVirusPandemicVirologyImmunologyNeuraminidase inhibitorInfluenza A virusInternal medicineDiseaseCoronavirus disease 2019 (COVID-19)Infectious disease (medical specialty)
DOInot available

Abstract

fetched live from OpenAlex

Influenza vaccination with current inactivated vaccines homologous to the prevalent wild-type virus can reduce influenza illness in 75%-80% of healthy adults. Vaccine is recommended for all individuals with chronic underlying diseases and for those aged 65 years or older. Although influenza vaccination is still advocated for patients with blunted immunity, protection rates are not as high, running at 40% for frail institutionalized elderly people. The influenza antiviral agents amantadine or rimantadine, zanamivir and oseltamivir can modify the severity of illness and reduce the duration of illness by about 1.5-2.5 days. Amantadine inhibits only influenza A. Resistant virus may emerge in up to 33% of amantadine-treated patients in the first 5 days of treatment and be transmitted to susceptible close contacts. Side effects are usually mild in short courses of treatment. The neuraminidase inhibitor drugs zanamivir and oseltamivir act on both influenza A and B. Treatment is most effective when given within 30-36 hours after the onset of illness, and the earlier the better. Influenza should be treated with antiviral drugs in unvaccinated and vaccinated high-risk patients, as well as immunosuppressed patients with influenza-like illness, in periods of confirmed influenza prevalence. These drugs may be of great value in the event of a major viral antigenic shift that causes pandemic influenza, if an adequate supply can be sustained.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.070
GPT teacher head0.329
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations154
Published2003
Admission routes1
Has abstractyes

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