435. Outcomes for E484K Mutation Negative COVID-19 Patients Cohorted with E484K Mutation Positive COVID-19 Patients: A Retrospective Cohort Study
Bibliographic record
Abstract
Abstract Background The emergence of the E484K mutation of SARS-CoV-2 poses a risk of immune evasion but the risk of re-infection during acute infection is not well defined. Our aim was to assess the risk of re-infection among patients with existing acute E484K mutation negative COVID-19 infection who were exposed to an E484K mutation positive SARS-CoV-2 infected patient. Methods We performed a retrospective cohort study of patients admitted with acute E484K negative COVID-19 infection and shared a hospital room with a patient who was E484K mutation positive during their period of communicability. The primary outcome was laboratory confirmed and/or clinical evidence of re-infection within the E484K negative population within 30 days of exposure and the secondary outcome was the 30-day risk of death or re-admission to hospital due to COVID-19. Results We identified 41 patients who were E484K mutation negative who shared a hospital room with some of the identified 34 E484K positive patients. Six (14%) underwent repeat COVID-19 testing and remained E484K negative and none developed signs or symptoms of COVID-19 re-infection during the 30 days following exposure. The mortality rate was 7% (3/41) and re-admission rate was zero at 30 days from exposure. Conclusion Despite the small sample size, we did not observe any evidence of re-infection among patients with COVID-19 who shared a hospital room with E484K positive patients during their acute infection. If necessary due to high hospital occupancy, patients with discordant E484K results can be safely cohorted in a shared room. Disclosures All Authors: No reported disclosures
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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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".