Current and Past Immunodeficiency Are Associated with Higher Hospitalization Rates among Persons on Virologically Suppressive Antiretroviral Therapy for up to 11 Years
Bibliographic record
Abstract
Background: Persons with human immunodeficiency virus (PWH) with persistently low CD4 counts despite efficacious antiretroviral therapy could have higher hospitalization risk. Methods: In 6 US and Canadian clinical cohorts, PWH with virologic suppression for ≥1 year in 2005-2015 were followed until virologic failure, loss to follow-up, death, or study end. Stratified by early (years 2-5) and long-term (years 6-11) suppression and lowest presuppression CD4 count <200 and ≥200 cells/μL, Poisson regression models estimated hospitalization incidence rate ratios (aIRRs) comparing patients by time-updated CD4 count category, adjusted for cohort, age, gender, calendar year, suppression duration, and lowest presuppression CD4 count. Results: The 6997 included patients (19 980 person-years) were 81% cisgender men and 40% white. Among patients with lowest presuppression CD4 count <200 cells/μL (44%), patients with current CD4 count 200-350 vs >500 cells/μL had aIRRs of 1.44 during early suppression (95% confidence interval [CI], 1.01-2.06), and 1.67 (95% CI, 1.03-2.72) during long-term suppression. Among patients with lowest presuppression CD4 count ≥200 (56%), patients with current CD4 351-500 vs >500 cells/μL had an aIRR of 1.22 (95% CI,. 93-1.60) during early suppression and 2.09 (95% CI, 1.18-3.70) during long-term suppression. Conclusions: Virologically suppressed patients with lower CD4 counts experienced higher hospitalization rates and could potentially benefit from targeted clinical management strategies.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".