CD4 percentage is an independent predictor of survival in patients starting antiretroviral therapy with absolute CD4 cell counts between 200 and 350 cells/μL
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To determine the prognostic value of baseline CD4 percentage in terms of patient survival in comparison to absolute CD4 cell counts for HIV-positive patients initiating highly active antiretroviral therapy (HAART). METHODS: A population-based cohort study of 1,623 antiretroviral therapy-naïve HIV-positive individuals who initiated HAART between 1 August 1996 and 30 June 2002 was conducted. Cumulative mortality rates were estimated using Kaplan-Meier methods. Cox proportional hazards regression was used to model the effect of baseline CD4 strata and CD4 percentage strata and other prognostic variables on survival. A subgroup analysis was conducted on 417 AIDS-free subjects with baseline CD4 counts between 200 and 350 cells/microL. RESULTS: In multivariate models, low CD4 percentages were associated with increased risk of death [CD4%<5, relative hazard (RH)=4.46; CD4% 5-14, RH=2.43; P<0.01 for both] when compared with those subjects with an initial CD4 fraction of 15% or greater, but had less predictive value than absolute CD4 counts. In subgroup analyses where absolute CD4 strata were not associated with mortality, a baseline CD4 fraction below 15% [RH=2.71; 95% confidence interval (CI) 1.20-6.10], poor adherence to therapy and baseline viral load >100,000 HIV-1 RNA copies/mL were associated with an increased risk of death. CONCLUSION: CD4 percentages below 15% are independent predictors of mortality in AIDS-free patients starting HAART, including those with CD4 counts between 200 and 350 cells/microL. CD4 percentage should be considered for inclusion in guidelines used to determine when to start therapy.
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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) | 0.001 | 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 it