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Record W2794154824 · doi:10.1080/21645515.2018.1445446

Seasonal influenza vaccine in immunocompromised persons

2018· review· en· W2794154824 on OpenAlexaff
Mohammad Bosaeed, Deepali Kumar

Bibliographic record

VenueHuman Vaccines & Immunotherapeutics · 2018
Typereview
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsImmunogenicityMedicineInfluenza vaccineVaccinationImmunologyLive attenuated influenza vaccinePopulationDiseaseImmune systemInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Immunocompromised persons are at high risk of complications from influenza infection. This population includes those with solid organ transplants, hematopoietic stem cell transplants, solid cancers and hematologic malignancy as well as those with autoimmune conditions receiving biologic therapies. In this review, we discuss the impact of influenza infection and evidence for vaccine effectiveness and immunogenicity. Overall, lower respiratory disease from influenza is common; however, vaccine immunogenicity is low. Despite this, in some populations, influenza vaccine has demonstrated effectiveness in reducing severe disease. Various strategies to improve influenza vaccine immunogenicity have been attempted including two vaccine doses in the same influenza season, intradermal, adjuvanted, and high-dose vaccines. The timing of influenza vaccine is also important to achieve optimal immunogenicity. Given the suboptimal immunogenicity, family members and healthcare professionals involved in the care of these populations should be vaccinated. Health care professional recommendation for vaccination is an important factor in vaccine coverage.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.204
GPT teacher head0.458
Teacher spread0.255 · 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

Citations146
Published2018
Admission routes1
Has abstractyes

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