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Record 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 on 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

Bibliographic record

VenueOpen Forum Infectious Diseases · 2017
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsSaint 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
Fundersnot available
KeywordsMedicineVaccinationIntensive care unitLogistic regressionEmergency medicineOdds ratioComorbidityInternal medicineInfluenza vaccineMechanical ventilationConfidence intervalIntensive care medicineImmunology

Abstract

fetched live from 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

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.406
Threshold uncertainty score0.816

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.014
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.393
Teacher spread0.354 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
Admission routes2
Has abstractyes

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