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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 OpenAlex
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

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

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.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.194
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