Effect of Baseline CD4 Cell Counts on the Clinical Significance of Short-Term Immunologic Response to Antiretroviral Therapy in Individuals With Virologic Suppression
Bibliographic record
Abstract
BACKGROUND: Achieving virologic suppression is a clear therapeutic goal for patients receiving combination antiretroviral therapy (cART). However, the effects of immunologic responses, whether measured as CD4 count changes from baseline or CD4 counts at follow-up, in patients with virologic suppression, have not been clearly established. METHODS: Treatment-naive individuals aged > or =16 years, who initiated cART between 1998 and 2005 in participating cohorts of the ART Cohort Collaboration and achieved viral load < or =400 copies per milliliter 6 months after cART initiation, were included. We used Cox models to examine associations of CD4 change from baseline to 6 months, and absolute CD4 counts at 6 months, with subsequent rates of mortality and AIDS. Analyses were stratified by baseline CD4 count. RESULTS: Among 23,679 eligible participants, the median increase in CD4 count at 6 months, and the implications of these increases for subsequent mortality and AIDS, varied with baseline CD4 count. Mortality hazard ratios for increases of 0-50 cells per microliter, compared with >100 cells per microliter, were 1.87 (95% confidence interval: 1.28 to 2.73), 1.60 (1.13 to 2.28), 0.98 (0.58 to 1.65) and 1.24 (0.70 to 2.18) in participants with baseline CD4 cell count <50, 50-199, 200-349 and > or =350 cells per microliter, respectively. In contrast, hazard ratios for mortality or AIDS associated with absolute CD4 cell counts at 6 months were similar across all but the highest baseline CD4 cell count strata. CONCLUSION: It is not possible to derive thresholds for change in CD4 count that define an adequate immunologic response in individuals receiving cART. Absolute CD4 counts at 6 months are a more useful measure of immunologic response and subsequent prognosis.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".