Humoral immune responses to COVID-19 vaccination in people living with HIV receiving suppressive antiretroviral therapy
Bibliographic record
Abstract
Abstract Humoral responses to COVID-19 vaccines in people living with HIV (PLWH) remain incompletely characterized. We measured circulating antibodies against the SARS-CoV-2 spike protein receptor-binding domain (RBD), ACE2 displacement and viral neutralization activities one month following the first and second COVID-19 vaccine doses, and again 3 months following the second dose, in 100 adult PLWH and 152 controls. All PLWH were receiving suppressive antiretroviral therapy, with median CD4+ T-cell counts of 710 (IQR 525–935) cells/mm 3 , though nadir CD4+ T-cell counts ranged as low as <10 cells/mm 3 . After adjustment for sociodemographic, health and vaccine-related variables, HIV infection was associated with lower anti-RBD antibody concentrations and ACE2 displacement activity after one vaccine dose. Following two doses however, HIV was not significantly associated with the magnitude of any humoral response after multivariable adjustment. Rather, older age, a higher burden of chronic health conditions, and dual ChAdOx1 vaccination were associated with lower responses after two vaccine doses. No significant correlation was observed between recent or nadir CD4+ T-cell counts and responses to two vaccine doses in PLWH. These results indicate that PLWH with well-controlled viral loads and CD4+ T-cell counts in a healthy range generally mount strong initial humoral responses to dual COVID-19 vaccination. Factors including age, co-morbidities, vaccine brand, response durability and the rise of new SARS-CoV-2 variants will influence when PLWH will benefit from additional doses. Further studies of PLWH who are not receiving antiretroviral treatment or who have low CD4+ T-cell counts are needed, as are longer-term assessments of response durability.
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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 | 0.002 |
| 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 | 0.001 |
| 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".