RETRACTED ARTICLE:The impact of repeated vaccination on influenza vaccine effectiveness: a systematic review and meta-analysis
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
BACKGROUND: Conflicting results regarding the impact of repeated vaccination on influenza vaccine effectiveness (VE) may cause confusion regarding the benefits of receiving the current season's vaccine. METHODS: We systematically searched MEDLINE, Embase, PubMed, and Cumulative Index to Nursing and Allied Health Literature from database inception to August 17, 2016, for observational studies published in English that reported VE against laboratory-confirmed influenza for four vaccination groups, namely current season only, prior season only, both seasons, and neither season. We pooled differences in VE (∆VE) between vaccination groups by influenza season and type/subtype using a random effects model. The study protocol is registered with PROSPERO (registration number: CRD42016037241). RESULTS: We identified 3435 unique articles, reviewed the full text of 634, and included 20 for meta-analysis. Compared to prior season vaccination only, vaccination in both seasons was associated with greater protection against influenza H1N1 (∆VE = 26%; 95% CI, 15% to 36%) and B (∆VE = 24%; 95% CI, 7% to 42%), but not H3N2 (∆VE = 10%; 95% CI, -6% to 25%). Compared to no vaccination for either season, individuals who received the current season's vaccine had greater protection against H1N1 (∆VE = 61%; 95% CI, 50% to 70%), H3N2 (∆VE = 41%; 95% CI, 33% to 48%), and B (∆VE = 62%; 95% CI, 54% to 68%). We observed no differences in VE between vaccination in both seasons and the current season only for H1N1 (∆VE = 4%; 95% CI, -7% to 15%), H3N2 (∆VE = -12%; 95% CI, -27% to 4%), or B (∆VE = -8%; 95% CI, -17% to 1%). CONCLUSIONS: From the patient perspective, our results support current season vaccination regardless of prior season vaccination. We found no overall evidence that prior season vaccination negatively impacts current season VE. It is important that future VE studies include vaccination history over multiple seasons in order to evaluate repeated vaccination in more detail.
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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 | 0.024 | 0.115 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".