Clinical impact of altered T-cell homeostasis in treated HIV patients enrolled in a large observational cohort
Bibliographic record
Abstract
OBJECTIVE(S): We investigated the probability of transitioning in or out of the CD3⁺ T-cell homeostatic range during antiretroviral therapy, and we assessed the clinical impact of lost T-cell homeostasis (TCH) on AIDS-defining illnesses (ADIs) or death. DESIGN: Within the Canadian Observational Cohort (CANOC), we studied 4463 antiretroviral therapy (ART)-naive HIV-positive patients initiating combination ART (cART) between 2000 and 2010. METHODS: CD3⁺ trajectories were estimated using a four state Markov model. CD3⁺ T-cel percentage states were classified as follows: very low (<50%), low (50-64%), normal (65-85%), and high (>85%). Covariates associated with transitioning between states were examined. The association between CD3⁺ T-cell percentage states and time to ADI/death from cART initiation was determined using Cox proportional hazards models. RESULTS: A total of 4463 patients were followed for a median of 3 years. Two thousand, five hundred and eight (56%) patients never transitioned from their baseline CD3⁺ T-cell percentage state; 85% of these had normal TCH. In multivariable analysis, individuals with time-updated low CD4⁺ cell count, time-updated detectable viral load, older age, and hepatitis C virus (HCV) coinfection were less likely to maintain TCH. In the multivariable proportional hazards model, both very low and high CD3⁺ T-cell percentages were associated with increased risk of ADI/death [adjusted hazard ratio=1.91 (95% confidence interval, CI: 1.27-2.89) and hazard ratio=1.49 (95% CI: 1.13-1.96), respectively]. CONCLUSION: Patients with very low or high CD3⁺ T-cell percentages are at risk for ADIs/death. To our knowledge, this is the first study linking altered TCH and morbidity/mortality in cART-treated HIV-positive patients.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".