Impact of COVID-19 Infection Among Heart Transplant Recipients: A Southern Brazilian Experience
Bibliographic record
Abstract
PURPOSE: The coronavirus-2019 (COVID-19) infection is associated with a high risk of complications and death among heart transplant recipients. However, most cohorts are from high-income countries, while data from Latin America are sparse. METHODS: This is a retrospective cohort of heart transplant recipients followed at a hospital in Rio Grande do Sul, Brazil, between March 1st 2020 and October 1st 2021. RESULTS: , 48% with hypertension, 43% with chronic kidney disease, 5% with diabetes, within 2 (1-4) years of post-transplant follow-up. At presentation, the main symptoms were fever (62%), myalgia (33%), cough (33%), headache (33%), and dyspnea (19%). Hospitalization was required for 13 (62%) patients, with a time from first symptoms to the admission of 5 (1-12) days. In 38%, supplementary oxygen was needed, 19% required intensive care, and 10% mechanical ventilation. Three (14%) were infected after at least a first dose of COVID-19 vaccine. The main complications were bacterial pneumonia (38%), renal replacement therapy (19%), sepsis (10%) and venous thromboembolism (10%). Immunosuppression therapy was modified in 48%, with a reduction in the majority (89%). Two (10%) patients died in the hospital due to refractory hypoxemia and multiple organ dysfunction. The incidence of COVID-19 among transplant patients was comparable to the general population in the State of Rio Grande do Sul with a peak in December 2020. CONCLUSION: Heart transplant recipients shown a high rate of COVID-19 infection in Southern Brazil, with typical symptom presentation in most cases. There was an elevated rate of hospitalization, supplementary oxygen support, and complications. In-hospital lethality among infected heart transplanted recipients was similar to previously reported data worldwide despite the high rates of infection in Latin America.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".