COVID-19 hospitalisations in immunocompromised individuals in the Omicron era: a population-based observational study using surveillance data in British Columbia, Canada
Bibliographic record
Abstract
Background: People with immune dysfunction are at higher risk of severe outcomes from COVID-19 infection, but relatively little epidemiologic information is available for mostly vaccinated population in the Omicron era. This population-based study compared relative risk of breakthrough COVID-19 hospitalisation among vaccinated people identified as clinically extremely vulnerable (CEV) vs non-CEV individuals before treatment became more widely available. Methods: COVID-19 cases and hospitalisations reported to the British Columbia Centre for Disease Control (BCCDC) between January 7, 2022 and March 14, 2022 were linked with data on their vaccination and CEV status. Case hospitalisation rates were estimated across CEV status, age groups and vaccination status. For vaccinated individuals, risk ratios for breakthrough hospitalisations were calculated for CEV and non-CEV populations matched on sex, age group, region, and vaccination characteristics. Findings: Among CEV individuals, a total of 5591 COVID-19 reported cases were included, among which 1153 were hospitalized. A third vaccine dose with mRNA vaccine offered additional protection against severe illness in both CEV and non-CEV individuals. However, 2- and 3-dose vaccinated CEV population still had a significantly higher relative risk of breakthrough COVID-19 hospitalisation compared with non-CEV individuals. Interpretation: Vaccinated CEV population remains a higher risk group in the context of circulating Omicron variant and may benefit from additional booster doses and pharmacotherapy. Funding: BC Centre for Disease Control and Provincial Health Services Authority.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".