Genotypic susceptibility score (GSS) and CD4+ T cell recovery in HIV-1 patients with suppressed viral load
Bibliographic record
Abstract
OBJECTIVES: HIV drug resistance, measured by the genotypic susceptibility score (GSS), has a deleterious effect on the virological outcome of HIV-1-infected patients. However, it is not known if GSS retains any predictive value for CD4 recovery in patients with suppressed viral load. METHODS: Four hundred and six patients on virological failure (>500 copies/mL) with GSS : <6 months prior to switch therapy who achieved undetectable plasma viral load (<50 copies/mL) within 1 year, remained undetectable >1 year on an unchanged regimen and had CD4 data available during entire follow-up were included. Adjusted and unadjusted analyses of all characteristics at switch related to CD4 recovery were made for three time frames: (i) 'switch-suppression'; (ii) 'suppression-1 year'; and (iii) 'switch-1 year'. RESULTS: Higher GSS was associated with a greater CD4 recovery between 'switch' and '1 year' in the unadjusted analysis (P = 0.010); however, the effect of GSS was no longer statistically significant after adjusting for pre-switch clinical (CD4 count and plasma viral load) and demographic variables. Furthermore, only a lower pre-switch CD4 count was associated with increased CD4 recovery in the 'suppression-1 year' period in both unadjusted and adjusted models. The main CD4 recovery occurred in 'switch-suppression' and the variables associated, both unadjusted and adjusted, were CD4 and plasma viral load at switch, maintaining a trend for GSS (P = 0.06). CONCLUSIONS: In individuals who re-suppressed HIV viraemia after switching therapy, regimens having a higher GSS were associated with improved CD4 recovery only during the period from switch to virological suppression, but, once viral load is re-suppressed, the GSS of the new regimen has no further effect on subsequent CD4 recovery.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".