Impact of Vaccination and Early Monoclonal Antibody Therapy on Coronavirus Disease 2019 Outcomes in Organ Transplant Recipients During the Omicron Wave
Bibliographic record
Abstract
BACKGROUND: Solid organ transplant (SOT) recipients are at high risk for complications from coronavirus disease 2019 (COVID-19) and vaccine breakthrough infections are common. We determined the effectiveness of ≥3 doses of mRNA vaccine and early monoclonal antibody therapy in reducing disease severity against the Omicron (B.1.1.529) variant. METHODS: Prospective cohort study of consecutive SOT recipients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection referred to our transplant center who were followed for at least 30 days. The primary outcome was supplemental oxygen requirement. Effectiveness of sotrovimab and ≥3 vaccine doses was estimated using adjusted risk ratios (RR). RESULTS: Three hundred adult organ transplant recipients were included. Seventy-one patients (24.1%) were hospitalized, 44 (14.9%) required supplemental oxygen, 19 (6.5%) were admitted to the intensive care unit (ICU), 15 (5.1%) required mechanical ventilation (MV), and 13 (4.4%) died. On multivariate analysis, age and multiple comorbidities were risk factors for oxygen requirement. Both receipt of ≥3 vaccine doses prior to SARS-CoV-2 infection and receipt of sotrovimab in the first 7 days of symptom onset was associated with a reduction in the need for supplemental oxygen (RR 0.30 [95% confidence interval {CI}: .17 to .54] and RR 0.24 (95% CI: .1 to .59), respectively]. For sotrovimab, the number needed to treat (NNT) to prevent one patient requiring oxygen was 6.64 (95% CI: 4.56-13.66). Both sotrovimab use and having received ≥3 vaccine doses were also associated with a shorter hospitalization length of stay. CONCLUSIONS: In a cohort of SOT recipients with Omicron variant COVID-19 infection, prior receipt of ≥3 mRNA vaccine doses and early monoclonal antibody therapy were independently associated with significantly reduced disease severity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".