Clinical practice guideline–supported administration of monoclonal antibody therapy for high-risk patients with COVID-19: Experience of a quaternary care centre
Bibliographic record
Abstract
Background: Immunocompromised patients remain at risk of progression to severe COVID-19 disease. Methods: We describe clinical COVID-19-related outcomes after administration of anti-SARS-CoV-2 monoclonal antibodies (mAb) following institutional clinical practice guidelines (CPGs) in 205 high-risk patients between November 2021 and April 2022 at a Canadian quaternary care centre. Results: Median patient age was 59 years; 102 (50%) were female. Eighty-two (40%) were transplant recipients, 47 (23%) patients had hematologic malignancies, 25 (12%) had solid organ malignancies, and 51 (25%) had another indication. Forty-eight (23%) had received fewer than two doses of anti-SARS-CoV-2 vaccines. The majority (80%) had mild disease at presentation with 14% moderate and 6% severe. Median time from symptom onset to mAb administration was 3 days (IQR 2.0-5.5 days). Of those who received mAb as outpatients, 90 (93%) had favourable clinical outcomes (no COVID-19-related hospitalizations or death within 3 months). Of those who received mAb as inpatients, 93 (86%) had favourable outcomes (discharged without COVID-19-related re-admission or death), 4% were re-admitted, and 10% died. In logistic regression analysis, only disease severity at time of mAb administration was associated with unfavourable outcomes. Fewer than two vaccine doses was not associated with unfavourable outcomes, suggesting potential benefit among the under-vaccinated. There was a significant difference in adherence to CPGs between administration of mAb in outpatients versus inpatients (adherent for 85% versus 58%, p < 0.001), where non-adherence occurred in cases of severe disease. Conclusion: CPG-supported mAb administration for management of COVID-19 in high-risk patients was associated with favourable clinical outcomes and may be a useful model to guide future therapies.
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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 | 0.003 | 0.013 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".