The prognostic value of baseline CD4+ cell count beyond 6 months of antiretroviral therapy in HIV-positive patients in a resource-limited setting
Bibliographic record
Abstract
OBJECTIVE: The risk of death is highest in the first few months after initiation of antiretroviral therapy (ART). We examined whether initial CD4 cell count maintains a strong prognostic value among patients with at least 6 months follow-up after the initiation of ART. DESIGN: Observational study of HIV patients in Uganda aged 14 years or older enrolled in 10 clinics across Uganda. METHODS: Baseline CD4 cell count of patients with more than 6 months of follow-up were stratified into categories (<50, 50-99, 100-149, 150-249, >250 cells/μl). A Kaplan-Meier survival analysis and Cox proportional hazards regression was used to model the associations between baseline CD4 cell count and mortality. RESULTS: Of 22 315 patients, 20 730 (92.8%) had more than 6 months of follow-up. Six hundred and eleven (2.9%) patients died during follow-up and 737 (3.6%) were lost to follow-up. Relative to a baseline CD4 cell counts of less than 50 cells/μl, the adjusted hazard ratios for death were 0.83 [95% confidence interval (CI) 0.67-1.02], 0.71 (95% CI 0.57-0.88), 0.52 (95% CI 0.42-0.64), and 0.55 (95% CI 0.42-0.70) favouring those with baseline CD4 cell counts of 50-99, 100-149, 150-249, and at least 250 cells/μl, respectively. Differing ages and male sex increased the likelihood of mortality. CONCLUSION: Among patients with more than 6 months of follow-up after initiation of ART, baseline CD4 cell count at initiation still has important prognostic value. This suggests that active engagement and earlier treatment initiation is important for long-term survival.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".