COVID-19 Vaccination, Hospitalization Rates, and Mortality Differ Between People with Diagnosed Immune Mediated Inflammatory Disease and the General Population: A Population-Based Study
Bibliographic record
Abstract
Background: Vaccination reduces Coronavirus disease-19 (COVID-19) infection severity. We evaluated COVID-19 vaccine uptake and effectiveness in people with immune mediated inflammatory diseases (pIMIDs) versus the general population. Methods: Using population-based administrative health records, we identified cohorts between 2004 and 2022 with an IMID (rheumatoid arthritis n = 10,405, systemic autoimmune rheumatic disease n = 5888, inflammatory bowel disease n = 7911, multiple sclerosis n = 3665, psoriasis n = 23,948) who were matched (1:5) by age, sex, and region to general population comparators (n = 243,490) without these IMIDs. Between 1 January 2021 and 31 March 2022, rates of COVID-19 vaccine administration, hospitalizations with COVID-19 (Hosp-C), and all-cause mortality were assessed amongst pIMIDs and comparators using multivariable models. Results: More pIMIDs were vaccinated than comparators (87.3% vs. 84.7%, p < 0.0001). IMID diagnosis, increasing age, female sex, higher socioeconomic status, urban residence, immunotherapy use, and comorbidities were associated with increased odds of receiving at least two vaccine doses. pIMIDs had higher rates of Hosp-C (79 per 100,000, 95% confidence interval (CI) 77.8–80.2) than comparators (51 per 100,000, 95% CI 50.5–51.3; rate ratio 1.55; 95% CI 1.53, 1.58) and greater mortality [pIMID 1758 deaths, 3.61%; comparators (6346 deaths, 2.61%), RR 1.39 95% CI 1.32, 1.46)]. In multivariable analyses, vaccinated status was associated with less Hosp-C (OR 0.27, CI 0.23, 0.32) and death (HR 0.27 CI 0.24, 0.29); the association did not differ between IMID and comparator groups. Conclusions: Although COVID-19 vaccination reduced the risk of Hosp-C and death in both pIMIDs and comparators, pIMIDs remained at higher risk for both. Since SARS-CoV-2 is now endemic, these findings may inform ongoing vaccination recommendations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".