Immunogenicity, Safety, and Breakthrough Severe Acute Respiratory Syndrome Coronavirus 2 Infections After Coronavirus Disease 2019 Vaccination in Organ Transplant Recipients: A Prospective Multicenter Canadian Study
Bibliographic record
Abstract
Background: Solid organ transplant (SOT) recipients are at risk for severe coronavirus disease 2019 (COVID-19), despite vaccination. Our study aimed to elucidate COVID-19 vaccine immunogenicity and evaluate adverse events such as hospitalization, rejection, and breakthrough infection in a SOT cohort. Methods: We performed a prospective, observational study on 539 adult SOT recipients (age ≥18 years old) recruited from 7 Canadian transplant centers. Demographics including transplant characteristics, vaccine types, and immunosuppression and events such as hospitalization, infection, and rejection were recorded. Follow ups occurred every 4-6 weeks postvaccination and at 6 and 12 months from first dose. Serum was processed from whole blood to measure anti-receptor binding domain (RBD) antibodies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein to assess immunogenicity. Results: The COVID-19 vaccines were found to be safe in SOT recipients with low rates of rejection requiring therapy (0.7%). Immunogenicity improved after the third vaccine dose, yet 21% developed no anti-RBD response. Factors such as older age, lung transplantation, chronic kidney disease, and shorter duration from transplant were associated with decreased immunogenicity. Patients with at least 3 doses were protected from hospitalization when experiencing breakthrough infections. Significantly increased anti-RBD levels were observed in patients who received 3 doses and had breakthrough infection. Conclusions: Three or four doses of COVID-19 vaccines were safe, increased immunogenicity, and protected against severe disease requiring hospitalization. Infection paired with multiple vaccinations significantly increased anti-RBD response. However, SOT populations should continue to practice infection prevention measures, and they should be prioritized for SARS-CoV-2 pre-exposure prophylactics and early therapeutics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".