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Record W2890910012 · doi:10.1093/ofid/ofy211

Should Sex Be Considered an Effect Modifier in the Evaluation of Influenza Vaccine Effectiveness?

2018· article· en· W2890910012 on OpenAlexafffundabout
Catharine Chambers, Danuta M. Skowronski, Caren Rose, Gaston De Serres, Anne‐Luise Winter, James A. Dickinson, Agatha N. Jassem, Jonathan B. Gubbay, Kevin Fonseca, Steven J. Drews, Hugues Charest, Christine Martineau, Martin Petric, Mel Krajden

Bibliographic record

VenueOpen Forum Infectious Diseases · 2018
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsProvincial Laboratory of Public HealthUniversity of TorontoUniversity of CalgaryUniversity of AlbertaUniversité LavalInstitut National de Santé Publique du QuébecCentre hospitalier universitaire de QuébecPublic Health OntarioUniversity of British ColumbiaBC Centre for Disease Control
FundersPublic Health OntarioBritish Columbia Centre for Disease ControlGlaxoSmithKlinePublic Health AgencyCanadian Institutes of Health ResearchF. Hoffmann-La RocheMinistère de la SantéMinistère de la Santé et des Services sociauxAlberta HealthInstitut National de Santé Publique du QuébecPublic Health Agency of CanadaPfizer
KeywordsMedicineConfidence intervalInfluenza vaccineDemographyVaccinationInternal medicineImmunology

Abstract

fetched live from OpenAlex

Abstract We investigated sex as a potential modifier of influenza vaccine effectiveness (VE) between 2010–2011 and 2016–2017 in Canada. Overall VE was 49% (95% confidence interval [CI], 43% to 55%) for females and 38% (95% CI, 28% to 46%) for males (absolute difference [AD], 11%; P = .03). Sex differences were greatest for influenza A(H3N2) (AD, 17%; P = .07) and B(Victoria) (AD, 20%; P = .08) compared with A(H1N1)pdm09 (AD, 10%; P = .19) or B(Yamagata) (AD, –3%; P = .68). They were also more pronounced in older adults ≥50 years (AD, 19%; P = .03) compared with those <20 years (AD, 4%; P = .74) or 20–49 years (AD, –1%; P = .90) but with variation by subtype/lineage. More definitive investigations of VE by sex and age are warranted to elucidate these potential interactions.

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)0.040
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.071
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.006
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.194
GPT teacher head0.488
Teacher spread0.294 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations32
Published2018
Admission routes3
Has abstractyes

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