COVID-19 in Solid Organ Transplantation: Results of the National COVID Cohort Collaborative
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Coronavirus disease 2019 (COVID-19) has resulted in significant morbidity and mortality in solid organ transplant (SOT) recipients. The National COVID Cohort Collaborative was developed to facilitate analysis of patient-level data for those tested for COVID-19 across the United States. METHODS: In this study, we identified a cohort of SOT recipients testing positive or negative for COVID-19 (COVID+ and COVID-, respectively) between January 1, 2020, and November 20, 2020. Univariable and multivariable logistic regression were used to determine predictors of a positive result among those tested. Outcomes following COVID-19 diagnosis were also explored. RESULTS: Of 18 121 SOT patients tested, 1925 were positive (10.6%). COVID+ SOT patients were more likely to have a kidney transplant and be non-White race. Comorbidities were common in all SOT patients but significantly more common in those who were COVID+. Of COVID+ SOT, 42.9% required hospital admission. COVID+ status was the strongest predictor of acute kidney injury (AKI), rejection, and graft failure in the 90 d after testing. A total of 40.9% of COVID+ SOT experienced a major adverse renal or cardiac event, 16.3% experienced a major adverse cardiac event, 35.3% experienced AKI, and 1.5% experienced graft loss. CONCLUSIONS: In the largest US cohort of COVID+ SOT recipients to date, we identified patient factors associated with the diagnosis of COVID-19 and outcomes following infection, including a high incidence of major adverse renal or cardiac event and AKI.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it