Association Between HIV-1 RNA Level and CD4 Cell Count Among Untreated HIV-Infected Individuals
Bibliographic record
Abstract
OBJECTIVES: We examined the significance of plasma HIV-1 RNA levels (or viral load alone) in predicting CD4 cell decline in untreated HIV-infected individuals. METHODS: Data were obtained from the British Columbia Centre for Excellence in HIV/AIDS. Participants included all residents who ever had a viral load determination in the province and who had never taken antiretroviral drugs (N = 890). We analyzed a total of 2074 viral load measurements and 2332 CD4 cell counts. Linear mixed-effects models were used to predict CD4 cell decline over time. RESULTS: Longitudinal viral load was strongly associated with CD4 cell decline over time; an average of 1 log(10) increase in viral load was associated with a 55-cell/mm(3) decrease in CD4 cell count. CONCLUSIONS: Our results support the combined use of CD4 cell count and viral load as prognostic markers in HIV-infected individuals before the introduction of antiretroviral therapy.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".