Association of HIV-1 load and CD4 lymphocyte count with mortality among untreated African children over one year of age
Bibliographic record
Abstract
OBJECTIVE: To examine the association of viral load and CD4 lymphocyte count with mortality among HIV-infected children over one year of age. DESIGN: A prospective study. HIV-infected children were enrolled during the first year of life and followed for more than 2 years at the Queen Elizabeth Central Hospital in Blantyre, Malawi (southeast Africa). METHODS: Morbidity and mortality information was collected every 3 months, and physical examination and blood testing (for viral level and CD4 cell percentage) were performed every 6 months. Kaplan-Meier analyses and proportional hazards models were used to estimate survival and to examine the association of primary predictors with mortality. RESULTS: Of 155 HIV-infected children originally enrolled, 115 (74%) had viral load testing and 82 (53%) had both viral load and CD4 cell percentage testing after their first year. Among children over one year of age, significant associations were found between mortality and the log10 viral load and CD4 cell percentage in both univariate and multivariate models. Independent of the CD4 cell value, a one unit log10 increase in HIV RNA level increased the hazard of child mortality by more than twofold. Children with low CD4 cell counts (< 15%) and high viral loads (> or = 250,000 copies/ml median value) had the worst survival; children with high CD4 cell counts (> or = 15%) and low viral loads (< 250,000 copies/ml) had the best survival. CONCLUSION: As in developed countries, viral load and CD4 cell count are the main predictors of mortality among African children. Making these tests available adds to the challenges to be considered if antiviral therapies were to be adopted in these countries.
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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".