Comparison of COVID-19 Hospitalization and Death Between Solid Organ Transplant Recipients and the General Population in Canada, 2020–2022
Bibliographic record
Abstract
Background: Solid organ transplant recipients have a high risk of severe outcomes from SARS-CoV-2 infection. A comprehensive understanding of the impact of the COVID-19 pandemic across multiple waves in the solid organ transplant population and how this compares to the general population is limited. We conducted a population-based cohort study using linked administrative healthcare databases from Ontario, Canada to answer this question. Methods: We included 15 306 solid organ transplant recipients and 12 160 904 individuals from the general population. Our primary outcome was the rate (per 100 person-years) of severe COVID-19 (ie, hospitalization or death with a positive SARS-CoV-2 test) occurring between January 25, 2020, and November 30, 2022. Results: Compared with the general population, solid organ transplant recipients had almost a 6 times higher rate of severe COVID-19 (20.39 versus 3.44 per 100 person-years), with almost 5.5 times as high a rate of death alone (4.19 versus 0.77 per 100 person-years). Transplant recipients with severe COVID-19 were substantially younger (60.1 versus 66.5 y) and had more comorbidities. The rate of severe COVID-19 declined over time in the solid organ transplant population, with an incidence rate of 41.25 per 100 person-years in the first wave (January 25, 2020, to August 31, 2020) and 18.41 in the seventh wave (June 19, 2022, to November 30, 2022, Omicron era). Conclusions: Solid organ transplant recipients remain at high risk of severe outcomes when they are infected with SARS-CoV-2. Resources and strategies to mitigate the impact of SARS-CoV-2 exposure are needed in this vulnerable patient 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".