Influenza vaccination for healthcare workers who care for people aged 60 or older living in long-term care institutions
Notice bibliographique
Résumé
BACKGROUND: Healthcare workers' influenza rates are unknown but may be similar to those of the general public. Healthcare workers may transmit influenza to patients. OBJECTIVES: To identify all randomised controlled trials (RCTs) and non-RCTs assessing the effects of vaccinating healthcare workers on the incidence of laboratory-proven influenza, pneumonia, death from pneumonia and admission to hospital for respiratory illness in those aged 60 years or older resident in long-term care institutions (LTCIs). SEARCH METHODS: We searched CENTRAL 2013, Issue 2, MEDLINE (1966 to March week 3, 2013), EMBASE (1974 to March 2013), Biological Abstracts (1969 to March 2013), Science Citation Index-Expanded (1974 to March 2013) and Web of Science (2006 to March 2013). SELECTION CRITERIA: Randomised controlled trials (RCTs) and non-RCTs of influenza vaccination of healthcare workers caring for individuals aged 60 years or older in LTCIs and the incidence of laboratory-proven influenza and its complications (lower respiratory tract infection, or hospitalisation or death due to lower respiratory tract infection) in individuals aged 60 years or older in LTCIs. DATA COLLECTION AND ANALYSIS: Two authors independently extracted data and assessed risk of bias. MAIN RESULTS: We identified four cluster-RCTs (C-RCTs) (n = 7558) and one cohort study (n = 12,742) of influenza vaccination for HCWs caring for individuals ≥ 60 years in LTCFs. Three RCTs (5896 participants) provided outcome data that met our criteria. These three studies were comparable in study populations, intervention and outcome measures. The studies did not report adverse events. The principal sources of bias in the studies related to attrition and blinding. The pooled risk difference (RD) from the three cluster-RCTs for laboratory-proven influenza was 0 (95% confidence interval (CI) -0.03 to 0.03) and for hospitalisation was RD 0 (95% CI -0.02 to 0.02). The estimated risk of death due to lower respiratory tract infection was also imprecise (RD -0.02, 95% CI -0.06 to 0.02) in individuals aged 60 years or older in LTCIs. Adjusted analyses which took into account the cluster design did not differ substantively from the pooled analysis with unadjusted data. AUTHORS' CONCLUSIONS: The results for specific outcomes: laboratory-proven influenza or its complications (lower respiratory tract infection, or hospitalisation or death due to lower respiratory tract illness) did not identify a benefit of healthcare worker vaccination on these key outcomes. This review did not find information on co-interventions with healthcare worker vaccination: hand-washing, face masks, early detection of laboratory-proven influenza, quarantine, avoiding admissions, antivirals and asking healthcare workers with influenza or influenza-like-illness (ILI) not to work. This review does not provide reasonable evidence to support the vaccination of healthcare workers to prevent influenza in those aged 60 years or older resident in LTCIs. High-quality RCTs are required to avoid the risks of bias in methodology and conduct identified by this review and to test further these interventions in combination.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,006 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 source (Gemma direct ou Codex distillé), 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 ».