People with HIV receiving suppressive antiretroviral therapy show typical antibody durability after dual COVID-19 vaccination, and strong third dose responses
Bibliographic record
Abstract
Background: Longer-term humoral responses to two-dose COVID-19 vaccines remain incompletely characterized in people living with HIV (PLWH), as do initial responses to a third dose. Methods: We measured antibodies against the SARS-CoV-2 spike protein receptor-binding domain, ACE2 displacement and viral neutralization against wild-type and Omicron strains up to six months following two-dose vaccination, and one month following the third dose, in 99 PLWH receiving suppressive antiretroviral therapy, and 152 controls. Results: Though humoral responses naturally decline following two-dose vaccination, we found no evidence of lower antibody concentrations nor faster rates of antibody decline in PLWH compared to controls after accounting for sociodemographic, health and vaccine-related factors. We also found no evidence of poorer viral neutralization in PLWH after two doses, nor evidence that a low nadir CD4+ T-cell count compromised responses. Post-third-dose humoral responses substantially exceeded post-second-dose levels, though anti-Omicron responses were consistently weaker than against wild-type.Nevertheless, post-third-dose responses in PLWH were comparable to or higher than controls. An mRNA-1273 third dose was the strongest consistent correlate of higher post-third-dose responses. Conclusion: PLWH receiving suppressive antiretroviral therapy mount strong antibody responses after two- and three-dose COVID-19 vaccination. Results underscore the immune benefits of third doses in light of Omicron.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".