Effectiveness of a Fourth COVID-19 mRNA Vaccine Dose Against the Omicron Variant in Solid Organ Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: The effectiveness of booster doses of COVID-19 vaccines in solid organ transplant recipients is unclear. We conducted a population-based matched cohort study using linked administrative healthcare databases from Ontario, Canada to estimate the marginal vaccine effectiveness of a fourth versus third dose of the BNT162b2 and mRNA-1273 vaccines against clinically important outcomes (ie, hospitalization or death) and infection during the era of the Omicron variant. METHODS: We matched 3120 solid organ transplant recipients with a third COVID-19 vaccine dose (reference) to 3120 recipients with a fourth dose. Recipients were matched on the third dose date (±7 d). We used a multivariable Cox proportional hazards model to estimate the marginal vaccine effectiveness with outcomes occurring between December 21, 2021 and April 30, 2022. RESULTS: The cumulative incidence of COVID-19-related hospitalization or death was 2.8% (95% confidence interval [CI], 2.0-3.7) in the third dose group compared with 1.1% (95% CI, 0.59-1.8) in the fourth dose group after 84 d of follow-up (P < 0.001). The adjusted marginal vaccine effectiveness was 70% (95% CI, 47-83) against clinically important outcomes and 39% (95% CI, 21-52) against SARS-CoV-2 infection. CONCLUSIONS: Compared with a third dose, a fourth dose of the COVID-19 vaccine was associated with improved protection against hospitalization, death, and SARS-CoV-2 infection during the Omicron era. Results highlight the importance of a booster COVID-19 vaccine dose in solid organ transplant recipients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".