Outcomes of SARS-CoV-2 Infection in Unvaccinated Compared With Vaccinated Solid Organ Transplant Recipients: A Propensity Matched Cohort Study
Bibliographic record
Abstract
BACKGROUND: Solid organ transplant (SOT) recipients are at high risk for complications from coronavirus disease 2019 (COVID-19). Vaccination may mitigate this risk; however, immunogenicity appears to be significantly impaired, with reports of increased risk of breakthrough infection. It is unknown if vaccine breakthrough infections are milder or as severe as infections in unvaccinated patients. METHODS: We performed a multicenter matched cohort study between March 2020 and September 2021 to assess influence of COVID-19 vaccination on outcomes of COVID-19 infection. Treatment characteristics and disease severity outcomes were compared on the basis of vaccine status; breakthrough infections versus unvaccinated infections. Variable ratio propensity score matching based on age, sex, transplant type, and number of comorbidities, was used to develop the analytic cohort. Logistic regression was used to assess the influence of vaccination status on the selected outcomes. RESULTS: From a cohort of 511 SOT patients with COVID-19, we matched 77 partially or fully vaccinated patients with 220 unvaccinated patients. Treatment characteristics including use of dexamethasone, remdesivir, and antibiotics did not differ. Vaccinated participants were more likely to receive tocilizumab, 15 of 77 (19.5%) versus 5 of 220 (2.3%), P < 0.001. Disease severity outcomes including oxygen requirement, mechanical ventilation, and mortality were similar among medically attended vaccine breakthroughs compared with unvaccinated patients. CONCLUSIONS: SOT recipients who develop medically attended COVID-19 following 1- or 2-dose vaccination seem to have similar disease severity to unvaccinated patients who develop infection. This is consistent with the requirement that SOT recipients need 3 or more vaccine doses and emphasizes the importance of alternate strategies for this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".