MétaCan
Menu
← Back to cohort

High-Dose Versus Standard-Dose Influenza Vaccine and Cardiovascular Outcomes in Older Adults: The FLUNITY-HD Prespecified Pooled Analysis

2025· article· en· W4416079363 on OpenAlexaff
Niklas Dyrby Johansen, Daniel Modin, Jacobo Pardo‐Seco, Carmen Rodrı́guez-Tenreiro, Matthew M. Loiacono, Rebecca C. Harris, Marine Dufournet, Robertus van Aalst, Ayman Chit, Carsten Schade Larsen, Lykke Larsen, Lothar Wiese, Michael Dalager‐Pedersen, Brian Claggett, Kira Hyldekær Janstrup, Carmen Durán‐Parrondo, Marta Piñeiro-Sotelo, Martín Cribeiro-González, Mónica Conde-Pájaro, Susana Mirás‐Carballal, Juan‐Manuel González‐Pérez, Scott D. Solomon, Pradeesh Sivapalan, Cyril Jean‐Marie Martel, Jens‐Ulrik Stæhr Jensen, Federico Martinón‐Torres, Tor Biering‐Sørensen

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsOntario Drug Policy Research NetworkUniversity of Toronto
FundersXunta de GaliciaSanofi
KeywordsPooled analysisIncidence (geometry)Influenza vaccineRandomized controlled trialRespiratory systemPooled varianceMeta-analysisMultivariate analysis

Abstract

fetched live from OpenAlex

BACKGROUND: The high-dose inactivated influenza vaccine (HD-IIV) has demonstrated superior protection against a range of hospitalization end points versus standard-dose inactivated influenza vaccine (SD-IIV), but its effectiveness against specific cardiovascular outcomes and in those with pre-existing cardiovascular disease (CVD) is not well elucidated. METHODS: In a prespecified secondary analysis of the FLUNITY-HD (Pooled Analysis of Methodologically Harmonized Pragmatic Randomized Trials of High-Dose vs. Standard-Dose Influenza Vaccine Against Severe Clinical Outcomes) individual-level pooled data set integrating 2 methodologically harmonized pragmatic, individually randomized trials conducted in Denmark and Spain, we investigated the relative vaccine effectiveness of HD-IIV versus SD-IIV against severe cardiovascular outcomes and according to pre-existing CVD among adults ≥65 years of age. Data were primarily obtained from routine health care databases, with follow-up from 14 days after vaccination to May 31 the following year. RESULTS: The pooled data set encompassed 466 320 individually randomized participants, of whom 107 700 (23.1%) had a history of CVD. HD-IIV reduced the incidence of hospitalization for influenza or pneumonia, cardiorespiratory disease, laboratory-confirmed influenza, and any cause compared with SD-IIV, irrespective of the presence or absence of pre-existing CVD ( P interaction >0.66 for all outcomes). Compared with the SD-IIV group, the HD-IIV group had a significantly lower incidence of hospitalization for any CVD (HD-IIV, 1.15%, versus SD-IIV, 1.24%; relative vaccine effectiveness, 6.6% [95% CI, 1.6–11.4]; P =0.010), hospitalization for any respiratory disease (HD-IIV, 0.92%, versus SD-IIV, 0.98%; relative vaccine effectiveness, 6.5% [95% CI, 0.7–11.9]; P =0.027), and hospitalization for heart failure (HD-IIV, 0.11%, versus SD-IIV, 0.15%; relative vaccine effectiveness, 21.3% [95% CI, 7.6–33.0]; P =0.003). CONCLUSIONS: In a prespecified pooled analysis of 466 320 individually randomized older adults, HD-IIV reduced the incidence of a wide range of severe cardiovascular and respiratory outcomes compared with SD-IIV, with consistent findings regardless of previous history of CVD. Among cardiovascular outcomes, the protective effect of HD-IIV versus SD-IIV was particularly pronounced against hospitalization for heart failure. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT06506812.

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)0.042
metaresearch head score (Gemma)0.048
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: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.048
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.039
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.040
GPT teacher head0.347
Teacher spread0.307 · 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
GenreEmpirical

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

Citations6
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCirculation→Same topicInfluenza Virus Research Studies→French-language works237,207→