Immunogenicity and safety of mixed COVID-19 vaccine regimens in patients with immune-mediated inflammatory diseases: a single-centre prospective cohort study
Bibliographic record
Abstract
OBJECTIVE: CoV-2 vaccines, we compared postvaccine antibody responses and IMID disease activity/states. DESIGN: Single-centre prospective cohort study. SETTING: Specialty ambulatory clinics in central Canada. PARTICIPANTS: People with inflammatory arthritis (n=78; 77% rheumatoid arthritis), systemic autoimmune rheumatic diseases (n=84; 57% lupus), inflammatory bowel disease (n=93; 43% Crohn's) and multiple sclerosis (n=72; 71% relapsing-remitting) (female 79.4%, white 84.7%, mean (SD) age 56.0 (14.3) years) received COVID-19 vaccinations between March 2021 and September 2022. PRIMARY OUTCOME: Postvaccination anti-spike, anti-receptor binding domain (anti-RBD) and anti-nucleocapsid (anti-NC) IgG antibodies tested by multiplex immunoassays compared across vaccine regimens and with responses in 370 age-matched and sex-matched vaccinated controls. SECONDARY OUTCOMES: COVID-19 infection and self-reported IMID disease activity/state. RESULTS: Most (216/327, 66.1%) received homologous messenger RNA (mRNA) (BNT162b2 or mRNA1273) vaccines, 2.4% received homologous ChAdOx1 and 30.6% received heterologous vaccines (23.9% ChAdOx1/mRNA, 6.4% heterologous mRNA) for their first two vaccines (V1, V2). Seroconversion rates were 52.0% (91/175) for post-V1 anti-spike and 58.9% (103/175) for anti-RBD; 91.5% (214/234) for post-V2 anti-spike and 90.2% (211/234) for anti-RBD; and were lower than controls (post-V2 anti-spike 98.1% (360/370), p<0.0001). Antibody titres decreased 3 months after V2 but increased 1 month after the third vaccine (V3) and 1 month after the fourth vaccine (V4) (BAU/mL median (IQR), anti-spike 1835 (2448) 1 month post-V2, 629.1 (883.4) 3 months post-V2, 4757.5 (7033.1) 1 month post-V3 and 4356.0 (9393.4) 1 month post-V4; anti-RBD 1686.8 (2199.44) 1 month post-V2, 555.8 (809.3) 3 months post-V2, 4280.3 (6380.6) 1 month post-V3 and 4792.2 (11 673.78) 1 month post-V4). If primed with a vector vaccine, an mRNA vaccine increased antibody titres to those comparable to homologous mRNA vaccines. Anti-RBD and anti-spike titres were higher in anti-NC seropositive (n=31; 25 participants) versus seronegative samples (BAU/mL median (IQR) anti-RBD 11 755.3 (20 373.1) vs 1248.0 (53 278.7); anti-spike 11 254.4 (15 352.6) vs 1313.1 (3106.6); both p<0.001). IMID disease activity/state and rates of self-reported moderate or severe IMID flare were similar across vaccinations. CONCLUSION: Heterologous COVID-19 vaccination improves seroconversion rates following a vector vaccine and does not lead to IMID disease flare. IMIDs benefit from at least three vaccines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".