Cytomegalovirus serostatus among people with <scp>HIV</scp>, characterizing the prevalence, risk factors, and association with immune recovery
Bibliographic record
Abstract
Abstract Introduction Cytomegalovirus (CMV) infection is common among people with HIV (PWH), and may be associated with negative outcomes. We aimed to identify the seroprevalence of CMV between 01 January 1998 and 01 June 2022 among PWH accessing care at the Southern Alberta Clinic (SAC) and the associated risk factors. We also aimed to assess the impact of CMV seropositivity on CD4+ T‐cells and CD4+/CD8+ ratio recovery among PWH who maintain HIV viral suppression. Methods Poisson regression models with robust variance estimated crude and adjusted prevalence ratios and 95% confidence intervals to identify risk factors for CMV seronegativity. Among PWH maintaining viral suppression, trends in the median CD4+ T‐cell count and CD4+/CD8+ ratio were visualized, and continuous time‐to‐event Cox proportional hazard models estimated hazards ratios (aHR) for CD4+ cell count recovery to ≥500 cells/mm 3 and CD4+/CD8+ ratio of >1 at 10 years by CMV serostatus. Results Among 3249 PWH, 2954 (91%) were CMV seropositive. CMV seronegativity was associated with younger ages, male sex, non‐Hispanic white race and an education of ≥12 years. While CMV seronegativity did not affect CD4+ T‐cell recovery following HIV viral suppression (aHR 1.15 [0.89–1.48]), it was associated with a greater likelihood of CD4+/CD8+ ratio normalization (aHR 2.38 [1.85–3.07]) at 10 years of follow‐up. Conclusions CMV is a common coinfection among PWH. We found that CMV positivity among PWH maintaining HIV viral suppression, while not associated with CD4+ T‐cell recovery, was associated with a reduced CD4+/CD8+ ratio recovery. This suggests an association with chronic CMV infection‐mediated immune activation and inflammation among PWH.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".