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Enregistrement W2549988362 · doi:10.1093/ofid/ofw194.75

Influenza Vaccine Effectiveness in the Prevention of Influenza-Related Hospitalization in Canadian Adults Over the 2011/12 Through 2013/14 Season: A Pooled Analysis From the Serious Outcomes Surveillance (SOS) Network of the Canadian Influenza Research Network (CIRN)

2016· article· en· W2549988362 sur OpenAlexaffabout
Shelly McNeil, Todd F. Hatchette, Melissa K. Andrew, Ardith Ambrose, Guy Boivin, Francisco Díaz‐Mitoma, William Bowie, Ayman Chit, Gaël Dos Santos, May ElSherif, Karen Green, François Haguinet, Scott A. Halperin, Barbara Ibarguchi, Jennie Johnstone, Kevin Katz, Joanne M. Langley, Jason J. LeBlanc, Philippe Lagacé‐Wiens, Bruce Light, Mark Loeb, Donna MacKinnon‐Cameron, Anne McCarthy, Janet E. McElhaney, Allison McGeer, André Poirier, Jeff Powis, David Richardson, Makeda Semret, Vivek Shinde, Stephanie Smith, Daniel Smyth, Grant Stiver, Geoff Taylor, Sylvie Trottier, Louis Valiquette, Duncan Webster, Lingyun Ye

Notice bibliographique

RevueOpen Forum Infectious Diseases · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueInfluenza Virus Research Studies
Établissements canadiensMoncton HospitalMcGill UniversityWilliam Osler Health SystemUniversité de SherbrookeToronto East General HospitalUniversity of Alberta HospitalOttawa HospitalCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-QuébecNorth York General HospitalMcMaster UniversityMount Sinai HospitalAlberta Hospital EdmontonUniversity of British ColumbiaDalhousie UniversityHorizon Health NetworkBayer (Canada)Health Sciences NorthIzaak Walton Killam Health CentreNova Scotia Health AuthorityCentre hospitalier universitaire de QuébecSt. Boniface Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineInfluenza seasonPooled analysisInfluenza vaccineFlu seasonEmergency medicineVaccinationIntensive care medicineEnvironmental healthFamily medicinePediatricsVirologyInternal medicineMeta-analysis

Résumé

récupéré en direct d'OpenAlex

Background. Ongoing assessment of influenza vaccine effectiveness (VE) is critical to inform public health decision making. The CIRN Serious Outcomes Surveillance (SOS) Network provides annual estimates of influenza VE in the prevention of influenza-associated hospitalization in adults. Here we provided pooled VE estimates across 3 influenza seasons. Methods. From 2011/12 to 2013/14, the CIRN SOS Network conducted active surveillance for influenza among hospitalized adults from ∼1 November to 30 April each season in up to 45 hospitals in 7 provinces. A nasopharyngeal swab for influenza polymerase chain reaction (PCR) was obtained from all patients admitted with any acute respiratory diagnosis or symptom. Cases were PCR-positive for influenza; test-negative controls matched for date and site of enrolment and age of the case (≥65 years versus <65 years) were enrolled for calculation of VE. VE was estimated as (1-odds ratio of influenza in vaccinated versus unvaccinated patients) × 100 for cases and controls enrolled over 3 seasons. VE estimates were adjusted using multivariable logistic regression with stepwise backward selection of covariates with a p value of <.1 in univariate analysis. Results. A total of 3394 cases and 4560 controls were enrolled; 2078 (61.2%) cases and 2939 (64.5%) controls were ≥65 years. Over 3 seasons, including all age groups, matched, adjusted VE was 41.7% (34.3–48.3%); VE in adults ≥65 years was 39.3% (29.4–47.8%) and in adults 16–64 years was 48.0% (37.5–56.7%). Including all age groups, VE against influenza A was 44.1% (35.1–51.9%) and against influenza B was 35.3% (20.7–47.3%). In adults ≥65 years, VE against influenza A/H3N2 and A/H1N1 was 24.2% (3.6–40.4) and 58.7% (39.4–71.9%), respectively. Corresponding estimates in 16–64 years were 44.4% (19.0%–61.8%) and 60.8% (45.1%–72%), respectively. Conclusion. While effectiveness of influenza vaccines to prevent serious outcomes varies year to year due to factors such as virulence and match between circulating and vaccine strains, here we demonstrate statistically and clinically important benefit of vaccination in adults spanning three seasons with an average overall effectiveness of 42%. The individual and public health benefit of influenza vaccines should not be understated and public messaging should address overall benefits over time while acknowledging year to year variability. Disclosures. S. A. McNeil, GSK: Grant Investigator, Research grant and Research support. Pfizer: Grant Investigator, Consulting fee, Research grant, Research support and Speaker honorarium. Merck: Consultant and Investigator, Consulting fee, Research support and Speaker honorarium; T. Hatchette, GSK: Investigator, Research grant; M. K. Andrew, GSK: Investigator, Research support; G. Boivin, Biocryst: Investigator, Research grant Merck: Investigator, Research grant; W. Bowie, GSK: Investigator, Research grant; A. Chit, Sanofi Pasteur: Employee, Salary; G. Dos Santos, Business and Decision Life Sciences: Consultant, Salary; F. Haguinet, GSK Vaccines: Employee, Salary; S. A. Halperin, GSK: Consultant, Grant Investigator and Research Contractor, Consulting fee and Grant recipient; B. Ibarguchi, GSK: Employee, Salary; J. M. Langley, GSK: Investigator, Research grant Sanofi Pasteur: Investigator, Research grant. PREVENT: Investigator, Research grant; P. Lagace-Wiens, Merck: Scientific Advisor, Consulting fee and Speaker honorarium; M. Loeb, GSK: Investigator, Research support; A. E. McCarthy, GSK: Investigator, Research support; J. E. McElhaney, GSK: Scientific Advisor, Research support and Speaker honorarium. Sanofi Pasteur: Scientific Advisor, Speaker honorarium; A. McGeer, GSK: Grant Investigator, Investigator and Scientific Advisor, Research support and Speaker honorarium. Sanofi Pasteur: Grant Investigator, Investigator and Scientific Advisor, Research support and Speaker honorarium. Merck: Grant Investigator, Investigator and Scientific Advisor, Research support and Speaker honorarium; A. Poirier, Actelion: Investigator, Research grant. Genetech: Investigator, Research grant. Sanofi Pasteur: Investigator, Research grant. Vertex: Investigator, Research grant; J. Powis, GSK: Investigator, Research support; V. Shinde, GSK: Employee, Salary

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,040
Score d'incertitude au seuil0,970

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,005
Études des sciences et des technologies0,0010,001
Communication savante0,0000,001
Science ouverte0,0020,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,029
Tête enseignante GPT0,362
Écart entre enseignants0,333 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2016
Routes d'admission2
Résumé présentoui

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