Factors associated with severe COVID-19 outcomes among adults with at least a primary vaccination schedule: a retrospective cohort study from Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: With a large proportion of adults in Canada vaccinated against SARS-CoV-2, it is important to identify who remain at risk for severe COVID-19 outcomes after primary vaccination and additional (booster) doses. METHODS: Adults (≥18 years) who received at least a primary vaccination schedule between December 2020 and March 2023 in Alberta, Canada were identified through population-level administrative data. Factors associated with severe COVID-19 outcomes (COVID-19 related hospitalization or death) were examined using univariable and multivariable Cox proportional hazard models. RESULTS: Among those who received a primary vaccination schedule (n = 2,639,731), 0.2% (n = 5,475) had ≥ 1 severe COVID-19 outcome. Factors associated with a greater risk of a severe COVID-19 outcome included older age (≥65 versus <65 years; unadjusted hazard ratio [95% confidence interval]: 8.83 [8.33-9.35]), and living with a higher comorbid burden (severe versus no burden; 32.56 [29.78-35.60]) or health condition of interest (1.33 [1.25-1.42] to 29.25 [23.14-36.99]) such as the relatively common condition of cardiovascular disease (7.01 [6.62-7.42]; present in 10.5% of the cohort) and less common condition of dementia (13.96 [12.76-15.28]; present in 1.5% of the cohort); male sex was also associated with risk (versus female; 1.07 [1.01-1.13]). Results remained significant in fully adjusted analysis, and among those with ≥1 additional vaccination dose (n = 1,580,110). CONCLUSION: Although primary vaccination and additional doses have dramatically reduced the occurrence of severe COVID-19 outcomes, results showed that continued risk remained for specific groups. Findings can be used to inform decision making, public health strategies, and policy development to protect those who remain at risk of severe COVID-19 outcomes after receipt of a primary vaccination schedule or additional doses, and support Canada's National Advisory Committee on Immunisation recommendations for specific groups to stay up to date with COVID-19 vaccination to protect against severe COVID-19 outcomes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".