Safety Monitoring of Health Outcomes following Influenza Vaccination during the 2023-2024 Season among U.S. Medicare Beneficiaries Aged 65 Years and Older
Bibliographic record
Abstract
ABSTRACT Background Influenza vaccination is widely recommended for individuals aged 6 months and older in the United States (U.S.). While the safety of annual influenza vaccines is well established, FDA conducts routine monitoring and evaluation of safety. This study assessed the safety of 2023-2024 influenza vaccines among elderly U.S. Medicare beneficiaries. Methods A self-controlled case series (SCCS) analysis compared incidence rate ratios (IRR) of anaphylaxis, encephalitis/encephalomyelitis/acute disseminated encephalomyelitis, Guillain-Barré syndrome (GBS), transverse myelitis, hemorrhagic stroke (HS), non-hemorrhagic stroke (NHS), transient ischemic attack (TIA), and NHS or TIA, following 2023-2024 seasonal influenza vaccinations in risk and control intervals among Medicare beneficiaries aged 65 years and older. We used conditional Poisson regression to estimate IRRs and 95% confidence intervals (CIs) adjusted for event-dependent observation time for certain outcomes, seasonality, and uncertainty from outcome misclassification where feasible. For health outcomes with statistically significant associations, we stratified results by concomitant vaccination status. Results We observed a total of 20,258,006 influenza vaccinees among the Medicare population, and no statistically significant elevations of risk for anaphylaxis, encephalitis/encephalomyelitis (with ADEM), GBS, HS, or TM. For the combined NHS/TIA outcome (22-42-day risk window), we observed a small elevation in risk that was statistically significant in both the Fee-For-Service (FFS) and Medicare Advantage (MA) populations that received a high-dose vaccine. This risk was also statistically significant among MA beneficiaries that received any influenza vaccine. Additionally, we observed a small statistically significant risk for the individual TIA outcome (22-42-day risk window) among the MA population that received any influenza vaccine. Conclusion Results from this study indicate that the benefits of seasonal influenza vaccines continue to outweigh the risks. The small statistically significant increased risk of stroke outcomes observed in the study must be carefully considered in light of the known benefits of influenza vaccination.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".