Sotrovimab Lowers the Risk of <scp>COVID</scp>‐19 Related Hospitalization or Death in a Large Population Cohort in the United Arab Emirates
Bibliographic record
Abstract
Sotrovimab, an anti-severe acute respiratory syndrome-coronavirus 2 monoclonal antibody is being utilized to prevent progression of coronavirus disease 2019 (COVID-19). Therefore, to understand its benefits, we have conducted a retrospective analysis of all non-hospitalized patients with symptomatic COVID-19 who received a single infusion of sotrovimab and/or oral favipiravir at any Dubai COVID-19 related healthcare center between July 1, 2021, and October 31, 2021. The main outcome was to evaluate the risk of hospitalization for patients with COVID-19 or all-cause death within 28 days of treatment initiation. In this analysis, which included 10,882 patients (1,135 in the sotrovimab group, 2,653 in the sotrovimab/favipiravir group, and 7,094 in the favipiravir group), sotrovimab or sotrovimab/favipiravir reduced the risk of hospitalization (13 patients (1.5%) in the sotrovimab group and 71 patients (2.9%) in the sotrovimab/favipiravir group vs. 251 patients (4%) in the favipiravir group; hazard ratio (HR) for sotrovimab: 0.16, 95% confidence interval (CI): 0.09-0.28, P < 0.001; and for sotrovimab/favipiravir, HR: 0.42, 95% CI: 0.32-0.56, P < 0.001), or death by day 28 from the start of treatment (no death in the sotrovimab group and 2 deaths in the the sotrovimab/favipiravir group vs. 10 deaths in the favipiravir group; odds ratio: 0.18, 95% CI: 0.04 to 0.81, P = 026). Safety was assessed in all the 3,788 patients in the sotrovimab and sotrovimab/favipiravir groups, and the reported adverse events were by 34 patients (<1%). In conclusion, sotrovimab was found to reduce the risk of progression of COVID-19 when administrated early to non-hospitalized patients with symptomatic COVID-19. No safety concern was detected.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".