Non-R5-tropic HIV-1 in subtype A1 and D infections were associated with lower pretherapy CD4+ cell count but not with PI/(N)NRTI therapy outcomes in Mbarara, Uganda
Bibliographic record
Abstract
BACKGROUND: Previous studies suggest that infection with non-R5-tropic subtype B HIV-1, compared with R5, is associated with a more rapid decline in CD4 cell count, but does not affect PI/(N)NRTI therapy outcome. Here, we explored clinical correlates associated with viral tropism in subtype A1 and D infections. METHODS: HIV-1 subtype A1 (n = 196) and D (n = 143) pretherapy plasma samples and up to 7.5 years of posttherapy virologic and CD4 data were collected from a cross-sectional cohort in Mbarara, Uganda. Tropism and subtype were inferred using env V3 (geno2pheno) and gp41 (RIP) Sanger sequences. For each subtype, R5 infection was compared with non-R5 in terms of: pretherapy viral load and CD4 cell count (Mann-Whitney tests), and therapy outcomes, including time to virologic suppression, postsuppression virologic rebound, CD4 decline and CD4 recovery (log-rank tests). RESULTS: A 94% of all patients in this study achieved virologic suppression within median 3 months posttherapy. In both subtypes, non-R5 infection was associated with lower pretherapy CD4 cell count (non-R5 vs. R5; A: median 57 vs. 147 cells/μl P = 0.005; D: 80 vs. 128 cells/μl P = 0.006). Multivariable linear regression confirmed that tropism, not subtype nor the interaction between subtype and tropism, was a significant predictor of pretherapy CD4 cell count (P < 0.0001). None of pretherapy viral load, time to virologic suppression, virologic rebound, CD4 decline nor CD4 recovery was significantly different (all P > 0.09). CONCLUSION: Regardless of HIV-1 subtype or tropism, the majority of patients in this Ugandan cohort responded to therapy, even though non-R5 infection was associated with lower pretherapy CD4 cell count.
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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".