A Canadian Perspective: Monoclonal Antibodies for Pre- and Post-Exposure Protection from COVID-19 in Vulnerable Patients with Hematological Malignancies
Bibliographic record
Abstract
Patients with hematological malignancies have an increased risk of serious outcomes following COVID-19 infection, suggesting broader protection is needed beyond vaccination. Monoclonal antibodies such as sotrovimab, casirivimab-imdevimab, and bamlanivimab have provided valuable options for the treatment of COVID-19 disease. More recently, monoclonal antibodies have been examined for the prevention of COVID-19 infection. The monoclonal antibody combination, tixagevimab-cilgavimab, was recently approved by Health Canada as pre-exposure prophylaxis against COVID-19 in individuals who are immunocompromised or where vaccination is not recommended. Prophylactic approaches such as the use of tixagevimab-cilgavimab, in addition to COVID-19 vaccination, may provide additional protection for patients with hematological malignancies who are at greater risk of serious outcomes from COVID-19 infection.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".