Corticosteroids as Adjunctive Therapy in the Treatment of Influenza: An Updated Cochrane Systematic Review and Meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Corticosteroids may be beneficial in sepsis, but uncertainty remains over their effects in severe influenza. This systematic review updates the current evidence regarding corticosteroids in the treatment of influenza and examines the effect of dose on outcome. DATA SOURCES: Electronic databases (MEDLINE, EMBASE, CINAHL, LILACS, CENTRAL, and Web of Science) and trial registries were searched to October 2018 for randomized controlled trials, quasi-experimental designs, and observational cohort studies reporting corticosteroid versus no corticosteroid treatment in individuals with influenza. STUDY SELECTION AND DATA EXTRACTION: Two researchers independently assessed studies for inclusion. Risk of bias was assessed using the Cochrane Risk of Bias tool (randomized controlled trials) or Newcastle-Ottawa Scale (observational studies). Where appropriate, we estimated the effect of corticosteroids by random-effects meta-analyses using the generic inverse variance method. Meta-regression analysis was used to assess the association of corticosteroid dose and mortality. DATA SYNTHESIS: We identified 30 eligible studies, all observational apart from one randomized controlled trial. Twenty-one observational studies were included in the meta-analysis of mortality, which suggested an adverse association with corticosteroid therapy (odds ratio, 3.90; 95% CI, 2.31-6.60; 15 studies; adjusted hazard ratio, 1.49; 95% CI, 1.09-2.02; six studies). Risk of bias assessment was consistent with potential confounding by indication. Pooled analysis of seven studies showed increased odds of hospital-acquired infection in people treated with corticosteroids (unadjusted odds ratio, 2.74; 95% CI, 1.51-4.95). Meta-regression of the effect of dose on mortality did not reveal an association, but reported doses of corticosteroids in included studies were high (mostly > 40 mg methylprednisolone [or equivalent] per day). CONCLUSIONS: Corticosteroid treatment in influenza is associated with increased mortality and hospital-acquired infection, but the evidence relates mainly to high corticosteroid doses and is of low quality with potential confounding by indication a major concern.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".