Evaluating in vivo effectiveness of sotrovimab for the treatment of Omicron subvariant BA.2 versus BA.1: a multicentre, retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: In vitro data suggested reduced neutralizing capacity of sotrovimab, a monoclonal antibody, against Omicron BA.2 subvariant. However, limited in vivo data exist regarding clinical effectiveness of sotrovimab for coronavirus disease 2019 (COVID-19) due to Omicron BA.2. METHODS: A multicentre, retrospective cohort study was conducted at three Canadian academic tertiary centres. Electronic medical records were reviewed for patients ≥ 18 years with mild COVID-19 (sequencing-confirmed Omicron BA.1 or BA.2) treated with sotrovimab between February 1 to April 1, 2022. Thirty-day co-primary outcomes included hospitalization due to moderate or severe COVID-19; all-cause intensive care unit (ICU) admission, and all-cause mortality. Risk differences (BA.2 minus BA.1 group) for co-primary outcomes were adjusted with propensity score matching (e.g., age, sex, vaccination, immunocompromised status). RESULTS: Eighty-five patients were included (15 BA.2, 70 BA.1) with similar baseline characteristics between groups. Adjusted risk differences were non-statistically significant between groups for 30-day hospitalization (- 14.3%; 95% confidence interval (CI): - 32.6 to 4.0%), ICU admission (- 7.1%; 95%CI: - 20.6 to 6.3%), and mortality (- 7.1%; 95%CI: - 20.6 to 6.3%). CONCLUSIONS: No differences were demonstrated in hospitalization, ICU admission, or mortality rates within 30 days between sotrovimab-treated patients with BA.1 versus BA.2 infection. More real-world data may be helpful to properly assess sotrovimab's effectiveness against infections due to specific emerging COVID-19 variants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".