Effectiveness of Three Doses of mRNA COVID-19 Vaccines in the Hemodialysis Population during the Omicron Period
Bibliographic record
Abstract
BACKGROUND: Coronavirus disease 2019 (COVID-19) vaccine effectiveness studies in the hemodialysis population have demonstrated that two doses of mRNA COVID-19 vaccines are effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severe complications when Alpha and Delta were predominant variants of concern. Vaccine effectiveness after a third dose versus two doses for preventing SARS-CoV-2 infection and severe COVID-19 in the hemodialysis population against Omicron is not known. METHODS: We conducted a retrospective cohort study in Ontario, Canada, between December 1, 2021, and February 28, 2022, in the maintenance hemodialysis population who had received two versus three doses of mRNA COVID-19 vaccines. COVID-19 vaccination, SARS-CoV-2 infection, and related hospitalization and death were determined from provincial databases. The primary outcome was the first RT-PCR confirmed SARS-CoV-2 infection, and the secondary outcome was a SARS-CoV-2-related severe outcome, defined as either hospitalization or death. RESULTS: A total of 8457 individuals receiving in-center hemodialysis were included. At study initiation, 2334 (28%) individuals received three doses, which increased to 7468 (88%) individuals by the end of the study period. The adjusted hazard ratios (aHR) for SARS-CoV-2 infection (aHR, 0.58; 95% confidence interval [CI], 0.50 to 0.67) and severe outcomes (hospitalization or death) (aHR, 0.40; 95% CI, 0.28 to 0.56) were lower after three versus two doses of mRNA vaccine. Prior infection, independent of vaccine status, was associated with a lower risk of reinfection, with an aHR of 0.44 (95% CI, 0.27 to 0.73). CONCLUSIONS: Three-dose mRNA COVID-19 vaccination was associated with lower incidence of SARS-CoV-2 infection and severe SARS-CoV-2-related outcomes during the Omicron period compared with two doses.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".