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6ER-003 Influenza vaccination and its association with dementia risk: a systematic review and meta-analysis

2025· review· en· W4408376389 on OpenAlexaboutno aff
Chia‐Chen Liu, SC Shao, Wen-Chen Yang, Ching‐Chi Chi

Bibliographic record

Venuenot available
Typereview
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisDementiaAssociation (psychology)VaccinationMedicineVirologyPsychologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Background and Importance Influenza vaccination is not only effective in preventing influenza but may also provide protection against other diseases, including dementia. While previous studies have explored the relationship between influenza vaccination and dementia, the association in populations with specific underlying conditions remains unclear. Aim and Objectives This systematic review and meta-analysis aimed to evaluate whether influenza vaccination is associated with a reduced risk of dementia, particularly in individuals with specific diseases. Material and Methods We systematically searched the relevant studies via MEDLINE and Embase from inception to 17 July 2024, using keywords and MeSH/Emtree terms related to dementia and influenza vaccination. The inclusion criteria were: (1) Population: Adults, (2) Exposure: Influenza vaccination, (3) Controls: No influenza vaccination, (3) Outcome: Risk estimates of dementia diagnosis, and (4) Study design: Cohort studies. Screening and data extraction were performed independently by two authors, with discrepancies resolved by a third author. The quality and risk of bias of the included studies were assessed using the Newcastle-Ottawa Scale. Dementia risk data were pooled using a random effects model, with hazard ratios (HRs) and 95% confidence intervals (CIs) as the primary outcome measure. Results Out of 447 studies identified, seven met the inclusion criteria, encompassing 8,265,275 participants (52.8% female). Six out of the seven included studies were judged to have a low-risk of bias. Pooled analysis indicated that influenza vaccination is associated with a lower risk of all-cause dementia (HR: 0.75; 95% CI, 0.66–0.85). This association was observed both in the general population (HR: 0.89; 95% CI, 0.81–0.98) and in those with specific diseases, including hypertension, diabetes mellitus, and dyslipidaemia (HR: 0.66; 95% CI, 0.63–0.69). Regarding vaccination doses, individuals receiving four or more doses demonstrated a significant reduction in dementia risk (e.g., HR: 0.42; 95% CI: 0.35–0.50). In terms of dementia subtypes, influenza vaccination was associated with a lower risk of vascular dementia (HR: 0.59; 95% CI: 0.47–0.75), but not with Alzheimer’s disease (HR: 0.87; 95% CI: 0.64–1.19). Conclusion and Relevance Influenza vaccination was associated with a reduced risk of dementia, particularly vascular dementia, and in populations with specific underlying conditions. These findings highlighted the potential of vaccination as a valuable strategy for dementia prevention in high-risk groups. References and/or Acknowledgements Conflict of Interest No conflict of interest

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.036
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.145
GPT teacher head0.444
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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