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Record W1972897249 · doi:10.4161/hv.23491

Vaccination against herpes zoster in developed countries

2013· review· en· W1972897249 on OpenAlexaff
Mélanie Drolet, Michael N. Oxman, Myron J. Levin, Kenneth E. Schmader, Robert W. Johnson, David M. Patrick, James A. Mansi, Marc Brisson

Bibliographic record

VenueHuman Vaccines & Immunotherapeutics · 2013
Typereview
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsBC Centre for Disease ControlUniversity of British ColumbiaUniversité LavalHôtel-Dieu de QuébecCentre hospitalier universitaire de Québec
FundersNational Institute on Aging
KeywordsVaccinationVirologyMedicineShinglesImmunologyEnvironmental healthVirus

Abstract

fetched live from OpenAlex

Although progress has been made in the treatment of herpes zoster (HZ) and postherpetic neuralgia (PHN), available therapeutic options are only partially effective. Given evidence that a live-attenuated varicella-zoster-virus vaccine is effective at reducing the incidence of HZ, PHN and the burden of illness, policymakers and clinicians are being asked to make recommendations regarding the use of the zoster vaccine. In this report, we summarize the evidence regarding the: (1) burden of illness; (2) vaccine efficacy and safety; and (3) cost-effectiveness of vaccination, to assist evidence-based policy making and guide clinicians in their recommendations. First, there is general agreement that the overall burden of illness associated with HZ and PHN is substantial. Second, the safety and efficacy of the zoster vaccine at reducing the burden of illness due to HZ and the incidence of PHN have been clearly demonstrated in large placebo-controlled trials. However, uncertainty remains about the vaccine's duration of protection. Third, vaccination against HZ is likely to be cost-effective when the vaccine is given at approximately 65 y of age, if vaccine duration is longer than 10 y.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.095
GPT teacher head0.395
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations27
Published2013
Admission routes1
Has abstractyes

Explore more

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