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Enregistrement W2751841713 · doi:10.1093/ofid/ofx162.046

Impact of Antivirals in the Prevention of Serious Outcomes Associated with Influenza in Hospitalized Canadian Adults: A Pooled Analysis from the Serious Outcomes Surveillance (SOS) Network of the Canadian Immunization Research Network (CIRN)

2017· article· en· W2751841713 sur OpenAlexaffabout
Zach Shaffelburg, Michaela Nichols, Lingyun Ye, Melissa K. Andrew, Ardith Ambrose, Guy Boivin, William Bowie, Ayman Chit, Gaël Dos Santos, May ElSherif, Karen Green, François Haguinet, Scott A. Halperin, Todd F. Hatchette, Barbara Ibarguchi, Jennie Johnstone, Kevin Katz, Joanne M. Langley, Jason J. LeBlanc, Philippe Lagacé‐Wiens, Mark Loeb, Donna MacKinnon‐Cameron, Anne McCarthy, Janet E. McElhaney, Allison McGeer, Jeff Powis, David Richardson, Makeda Semret, Vivek Shinde, Stephanie Smith, Daniel Smyth, Geoffrey Taylor, Sylvie Trottier, Louis Valiquette, Duncan Webster, Shelly McNeil

Notice bibliographique

RevueOpen Forum Infectious Diseases · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueInfluenza Virus Research Studies
Établissements canadiensSaint John Regional HospitalMoncton HospitalWilliam Osler Health SystemUniversity of Alberta HospitalOttawa HospitalUniversity of ManitobaNorth York General HospitalMcMaster UniversityMount Sinai HospitalMcGill UniversitySanofi (Canada)Alberta Hospital EdmontonUniversity of British ColumbiaIzaak Walton Killam Health CentreNova Scotia Health AuthorityCentre hospitalier universitaire de QuébecHealth Sciences NorthBayer (Canada)Université de SherbrookeToronto East General HospitalUniversity of TorontoDalhousie University
Organismes subventionnairesnon disponible
Mots-clésMedicineVaccinationIntensive care unitLogistic regressionEmergency medicineOdds ratioComorbidityInternal medicineInfluenza vaccineMechanical ventilationConfidence intervalIntensive care medicineImmunology

Résumé

récupéré en direct d'OpenAlex

Abstract Background Antiviral treatment of influenza in outpatient settings is associated with modest improvement in outcomes but benefit in inpatient settings remains unclear. We assessed the impact of antiviral treatment on the severe outcomes death and intensive care unit (ICU) admission and/or need for mechanical ventilation (MV) in hospitalized influenza patients. Methods Patients admitted to hospitals of the CIRN SOS Network with an acute respiratory illness from 2011/12–2013/14 who tested polymerase chain reaction (PCR) positive for influenza were included. Demographic and medical information were obtained from patient interview or the medical chart. Main outcomes of interest were ICU admission and/or need for MV, and death. Logistic regression with backwards stepwise selection was used to estimate odds ratios (ORs) and 95% confidence limits (CIs) for the association between antiviral use and severe outcomes overall, and stratified by time from symptom onset to antiviral start (<48hours, 48hours <5 days, 5–21 days). Results Over 3 influenza seasons, 4,679 patients were enrolled; 59% were aged ≥65 years, 52% were female, and 89% had a comorbidity. Influenza vaccination status was available for 4,019 (86%) patients, of whom 1,796 (45%) had received current season vaccine. Of 4,679 patients, 16% of patients were admitted to ICU and/or required MV and 9% died. Overall, 54% of hospitalized influenza patients received an antiviral; mean time from the onset of symptoms to antiviral start was 4.28 days (range: 0–21 days). Treatment with antivirals was associated with a significant reduction in admission to ICU and/or need for MV (OR = 0.10; 95% CI: 0.08–0.13; P < 0.001), but was not significantly associated with a reduction in death (P = 0.454) irrespective of time between symptom onset and start of antivirals. Conclusion In this study, treatment with antivirals in hospitalized patients with influenza was associated with a significant reduction in ICU admission and MV, even when initiated a mean of 4.28 days from symptom onset. Reduction in death was not demonstrated. These findings support current recommendations for antiviral use in hospitalized adults and suggest increased compliance with these guidelines may reduce morbidity and cost. Disclosures M. K. Andrew, GSK: Grant Investigator, Research grant; Pfizer: Grant Investigator, Research grant; Sanofi-Pasteur: Grant Investigator, Research grant; A. Chit, Sanofi pasteur: Employee, Salary; G. Dos Santos, GSK: Employee, Salary; Business and Decision Life Sciences (Contractor for GSK Vaccines): Independent Contractor, Salary; M. Elsherif, Canadian Institutes of Health Research: Investigator, Research grant; Public Health Agency of Canada: Investigator, Research grant; GSK: Investigator, Research grant; F. Haguinet, GSK: Employee, Salary; S. A. Halperin, GSK: Scientific Advisor, Consulting fee; GSK: Grant Investigator, Research grant; T. Hatchette, GSK: Grant Investigator, Grant recipient; Pfizer: Grant Investigator, Grant recipient; Abbvie: Speaker for a talk on biologics and risk of TB reactivation, Speaker honorarium; B. Ibarguchi, GSK: Employee, Salary; J. M. Langley, GSK: Investigator, Research grant; Canadian Institutes of Health Research: Investigator, Research grant; J. Mcelhaney, GSK: Scientific Advisor, Honorarium to institution; Sanofi pasteur: Scientific Advisor, Honorarium to institution; A. Mcgeer, Hoffman La Roche: Investigator, Research grant; GSK: Investigator, Research grant; Sanofi pasteur: Investigator, Research grant; J. Powis, Merck: Grant Investigator, Research grant; GSK: Grant Investigator, Research grant; Roche: Grant Investigator, Research grant; Synthetic Biologicals: Investigator, Research grant; M. Semret, GSK: Investigator, Research grant; Pfizer: Investigator, Research grant; V. Shinde, Novavax: Employee, Salary; GSK: Shareholder, Stocks; GSK: Employee, Salary; S. Trottier, Canadian Institutes of Health Research: Investigator, Research grant; L. Valiquette, GSK: Investigator, Research grant; S. McNeil, GSK: Contract Clinical Trials and Grant Investigator, Research grant; Merck: Contract Clinical Trials and Speaker’s Bureau, Speaker honorarium; Novartis: Contract Clinical Trials, No personal renumeration; Sanofi pasteur: Contract Clinical Trials, No personal renumeration

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,013
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,406
Score d'incertitude au seuil0,816

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,013
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0040,014
Bibliométrie0,0030,005
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,040
Tête enseignante GPT0,393
Écart entre enseignants0,354 · 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 source (Gemma direct ou Codex distillé), 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

Citations0
Publié2017
Routes d'admission2
Résumé présentoui

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