Risks of Non-Accidental Mortality by Baseline CD4 <sup>+</sup> T-Cell Strata in Hepatitis-C-Positive and -Negative Individuals Initiating Highly Active Antiretroviral Therapy
Bibliographic record
Abstract
BACKGROUND: Patients coinfected with hepatitis C virus (HCV) and HIV experience higher mortality rates than patients infected with HIV alone. We designed a study to determine whether risks for later mortality are similar for HCV-positive and HCV-negative individuals when subjects are stratified on the basis of baseline CD4+ T-cell counts. METHODS: Antiretroviral-naive individuals, who initiated highly active antiretroviral therapy (HAART) between 1996 and 2002 were included in the study. HCV-positive and HCV-negative individuals were stratified separately by baseline CD4+ T-cell counts of 50 cell/microl increments. Cox-proportional hazards regression was used to model the effect of these strata with other variables on survival. RESULTS: CD4+ T-cell strata below 200 cells/microl, but not above, imparted an increased relative hazard (RH) of mortality for both HCV-positive and HCV-negative individuals. Among HCV-positive individuals, after adjustment for baseline age, HIV RNA levels, history of injection drug use and adherence to therapy, only CD4+ T-cell strata of <50 cells/microl (RH=4.60; 95% confidence interval [CI] 2.72-7.76) and 50-199 cells/microl (RH=2.49; 95% CI 1.63-3.81) were significantly associated with increased mortality when compared with those initiating therapy at cell counts >500 cells/microl. The same baseline CD4+ T-cell strata were found for HCV-negative individuals. CONCLUSION: In a within-groups analysis, the baseline CD4+ T-cell strata that are associated with increased RHs for mortality are the same for HCV-positive and HCV-negative individuals initiating HAART. However, a between-groups analysis reveals a higher absolute mortality risk for HCV-positive individuals.
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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 | 0.000 |
| 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 | 0.001 |
| 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".