Seasonal influenza vaccination: Overcoming immunosenescence with enhanced vaccines
Bibliographic record
Abstract
Influenza causes substantial morbidity and mortality worldwide. Risks are increased in older adults aged 50–64 and ≥ 65 years. They are further exacerbated in those with age-related comorbidities. Immunosenescence (strictly defined here as detrimental age-related decline in the function of some or all parts of the immune system) is associated with increased susceptibility to influenza infection and more severe disease, a process that begins at approximately 50 years of age. Age-associated chronic low-level inflammation (inflammaging) may also increase influenza risk and is associated with more serious disease but may also enhance responses to high-dose vaccines in older adults. The frequency of comorbidities also increases with age. Frail older adults are at highest risk of influenza complications, but adults with high-risk comorbidities also show improved immune responses to enhanced influenza vaccines (high-dose, adjuvanted, recombinant). Moreover, clinical studies with some enhanced influenza vaccines show improved immunogenicity and greater efficacy or effectiveness, not only for persons aged ≥65 years but also in those aged 50–64 years. Reduced immunogenicity in persons aged 50–64 years may be even greater in those with comorbidities who would specifically benefit from receiving enhanced vaccines. Thus, accelerated immunosenescence, inflammaging, and chronic disease may place some adults aged 50–64 years at high risk of influenza, justifying meeting an unmet need in vaccination with enhanced vaccines normally used in persons ≥65 years of age.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".