Influenza Vaccination and Major Adverse Vascular Events in High-Risk Patients
Bibliographic record
Abstract
BACKGROUND: We sought to determine the association between influenza vaccination and major adverse vascular events because the association remains uncertain. METHODS AND RESULTS: A total of 31 546 participants were enrolled from 40 countries. Eligibility included age ≥55 years and known vascular disease. The primary outcome was a composite of death resulting from cardiovascular causes, myocardial infarction, or stroke during 4 influenza seasons (2003-2007). Influenza vaccination was associated with a lower risk of the outcome during 3 influenza seasons (defined using World Health Organization FluNet reports): 2004 to 2005 (adjusted odds ratio [OR], 0.62; 95% confidence interval [CI], 0.50-0.77), 2005 to 2006 (adjusted OR, 0.69; 95% CI, 0.53-0.91), and 2006 to 2007 (adjusted OR, 0.52; 95% CI, 0.42-0.65), the same years that circulating influenza matched the vaccine antigen. In 2003 to 2004, there was an incomplete match between circulating influenza and the vaccine antigen, and there was no association between influenza vaccination and the outcome (adjusted OR, 0.96; 95% CI, 0.73-1.27). However, tests of potential biases in the analyses revealed associations between influenza vaccination and outcome during noninfluenza seasons except 2003 to 2004. The summary ORs in the influenza season (OR, 0.65; 95% CI, 0.58-0.74]) and noninfluenza season (OR, 0.66; 95% CI, 0.57-0.76) were almost identical. The reduction in risk of noncardiovascular death associated with the influenza vaccine ranged from 73% to 79%. CONCLUSION: Although initial analyses suggest that influenza vaccination was associated with reduced risk of major adverse vascular events during influenza seasons when the influenza vaccine matched the circulating virus, sensitivity analyses revealed that risk of bias remained. A randomized trial is needed to definitively address this question.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".