Effectiveness of Influenza Vaccine in Preventing Death among Ontario Residents Aged ≥65 Years during 20 Seasons
Notice bibliographique
Résumé
Estimation of influenza vaccine effectiveness (VE) among older adults at high risk of serious complications of influenza infection is challenging. These challenges include identifying and adjusting for potential confounders. The rarity of documented influenza deaths, even among individuals at greatest risk, makes VE assessment for this outcome particularly difficult. Thus, population-level linkages of public health system records are helpful in estimating VE for preventing death. We conducted a retrospective cohort study from 1993 through 2013 among community-dwelling residents of Ontario aged ≥65 years. Eligible subjects were registered with Ontario’s publicly funded health insurance program, which provided universal, free access to physician services, hospital care, and vaccines; we excluded those with no contact with the health system during the prior 3 years. We assessed influenza VE for preventing death from any cause and death for which the primary cause was a respiratory or circulatory condition. Influenza vaccination was determined using physician and pharmacist billing claims. Temperature and influenza virus detection data were collected from provincial sources. Ratio-of-ratios models were used to estimate VE, by comparing marginal changes in outcome rates among vaccinated and unvaccinated groups at various levels of influenza circulation. We evaluated several methods of characterizing temporal variation in influenza circulation and several geographic scales for using influenza and temperature data in VE estimation models. During the 20-year study period, we estimated VE among a mean of 1.39 million subjects each season, of whom a mean of 51.9% were vaccinated. During weeks of high influenza A circulation, we estimated that VE for the prevention of any death was 16% (95% CI -6% to 38%) and for the prevention of a respiratory or circulatory death was 21% (95% CI 2% to 40%). The precision of VE estimates improved when regional-level rather than Ontario-wide temperature data were used. During weeks of influenza A circulation over 20 seasons, we found that modest but significant reductions in deaths with an underlying respiratory or circulatory cause occurred among Ontario residents aged ≥65 who received an influenza vaccine. All authors: No reported disclosures.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».