The relative effectiveness of a high-dose quadrivalent influenza vaccine vs standard-dose quadrivalent influenza vaccines in older adults in France: a retrospective cohort study during the 2021-22 influenza season
Bibliographic record
Abstract
Abstract Background High-dose quadrivalent influenza vaccine (HD-QIV) was introduced during the 2021/22 influenza season in France for adults aged ≥65 years as an alternative to standard-dose quadrivalent influenza vaccines (SD-QIV). This is the first study to estimate the relative vaccine effectiveness (rVE) of HD-QIV versus SD-QIV against influenza-related hospitalizations in France. Methods Community-dwelling individuals aged ≥65 years with reimbursed influenza vaccine claims during the 2021/22 influenza season were included from the French national health insurance database. Individuals were followed up from vaccination day to 30 June 2022, nursing home admission or death date. Baseline socio-demographic and health characteristics were identified from medical records over the 5 previous years. Hospitalizations due to influenza and other causes were recorded from 14 days after vaccination to end of follow-up. HD-QIV and SD-QIV vaccinees were matched using 1:4 propensity score matching with an exact constraint on age group, sex, week of vaccination and region. Incidence rate ratios (IRR) were estimated using zero-inflated Poisson or zero-inflated negative binomial regression models. Results We matched 405,385 (99.9%) HD-QIV to 1,621,540 SD-QIV vaccinees. HD-QIV was associated with a 23.3% (95%CI: 8.4–35.8) lower rate of influenza hospitalizations compared to SD-QIV. Post-matching, we observed higher rates in the HD-QIV group for hospitalizations non-specific to influenza and for negative control outcomes, suggesting residual confounding by indication. Conclusions HD-QIV was associated with lower influenza-related hospitalization rates versus SD-QIV, consistent with existing evidence, in the context of high SARS-CoV-2 circulation in France and likely prioritization of HD-QIV for older/more comorbid individuals.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".