High-dose influenza vaccine for elderly: a closer look into the real-world data
Bibliographic record
Abstract
Older adults are at increased risk of severe illness, hospitalization, and death due to influenza, making vaccination a key public health strategy. High-dose (HD) influenza vaccine has been recommended in several European countries to enhance protection in this vulnerable group. While clinical trials and observational studies have reported improved effectiveness of HD vaccine in preventing influenza-related outcomes, this advantage appears most consistent in individuals aged 75 and older. In contrast, evidence supporting the superiority of HD vaccine over standard-dose (SD) vaccines in the 65-74 age group (the "young-old") is limited and often not statistically significant. This review examined real-world effectiveness data comparing HD and SD influenza vaccines in elderly populations. While HD vaccines may provide added protection in the oldest age groups, SD vaccines continue to offer substantial and reliable protection, particularly among the 60-74 age range. HD vaccine is associated with higher rates of mild side effects and carries a significantly greater cost, which may limit its cost-effectiveness for broad use in the younger elderly population. Given that the majority of elderly individuals in developed countries fall within the 65-74 age group, a tailored vaccination approach may be more appropriate. Recommending HD vaccine primarily for those aged 75 and older, while offering SD vaccines to younger seniors, may help increase vaccine coverage without compromising protection. More real-world, age-stratified studies are needed to guide vaccination policies. Ultimately, any influenza vaccine is better than none, and SD vaccines remain an effective and accessible option for most older adults.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".