COVID-19 vaccine immunogenicity in people with HIV
Bibliographic record
Abstract
OBJECTIVES: Many vaccines require higher/additional doses or adjuvants to provide adequate protection for people with HIV (PWH). Our objective was to compare COVID-19 vaccine immunogenicity in PWH to HIV-negative individuals. DESIGN: In a Canadian multi-center prospective, observational cohort of PWH receiving at least two COVID-19 vaccinations, we measured vaccine-induced immunity at 3 and 6 months post 2nd and 1-month post 3rd doses. METHODS: The primary outcome was the percentage of PWH mounting vaccine-induced immunity [co-positivity for anti-IgG against SARS-CoV2 Spike(S) and receptor-binding domain proteins] 6 months post 2nd dose. Univariable and multivariable logistic regressions were used to compare COVID-19-specific immune responses between groups and within subgroups. RESULTS: Data from 294 PWH and 267 controls were analyzed. Immunogenicity was achieved in over 90% at each time point in both groups. The proportions of participants achieving comparable anti-receptor-binding domain levels were similar between the group at each time point. Anti-S IgG levels were similar by group at month 3 post 2nd dose and 1-month post 3rd dose. A lower proportion of PWH vs. controls maintained vaccine-induced anti-S IgG immunity 6 months post 2nd dose [92% vs. 99%; odds ratio: 0.14 (95% confidence interval: 0.03, 0.80; P = 0.027)]. In multivariable analyses, neither age, immune non-response, multimorbidity, sex, vaccine type, or timing between doses were associated with reduced IgG response. CONCLUSION: Vaccine-induced IgG was elicited in the vast majority of PWH and was overall similar between groups. A slightly lower proportion of PWH vs. controls maintained vaccine-induced anti-S IgG immunity 6 months post 2nd dose demonstrating the importance of timely boosting in this population.
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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 | 0.000 |
| 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) | 0.001 | 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 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".