Predictors of Long-Term Immunological Outcome in Rebounding Patients on Protease Inhibitor-Based HAART After Initial Successful Virologic Suppression: Implications for Timing to Switch
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Bibliographic record
Abstract
OBJECTIVE: To assess predictive factors of long-term immune restoration in patients who started protease inhibitor (PI)-based HAART and experienced virological rebound after initial complete success. METHOD: A retrospective longitudinal analysis of all HIV-infected patients who started their first PI-based HAART and reached viral load below 500 copies/mL was carried out in a large academic center in Italy. Patients were classified either as complete virologic responder (CR) or rebounders (REB) when confirmed plasma viremia was detected thereafter. Immunological outcome was the area under the curve (AUC) of the absolute CD4+ cell count change since the 8th month after treatment initiation (CD4+ T-cell AUC). Association between baseline characteristics, virological outcome, and CD4+ T-cell AUC was assessed by univariate and multivariate analysis. RESULTS: There were 374 patients who were included in the study. Mean follow-up was 30.2 months. There were 226/374 patients (60.4%) who remained CR while 148/374 (39.6%) presented at least one rebound (REB). Among REB patients, complete viral suppression was regained in 15/42 (35.7%) and 50/106 (47.1%) patients who underwent therapy changes or not, respectively. When multiple linear regression was carried out, previous nucleoside reverse transcriptase inhibitor (NRTI) experience and baseline CD4+ cell count below 350 cells/muL did not impair long-term immune restoration. The occurrence of rebound, its duration (> 18 months), and its magnitude (peak of viral load > 10,000 copies/mL) were independent negative prognostic factors. CONCLUSION: The occurrence of viral rebound is independently associated with significantly impaired long-term immunological restoration. The magnitude of viral rebound (< 10,000 copies/mL) and its duration (< 18 months) may be useful to identify those rebounding patients who may still profit from maintaining the current failing therapy if a more aggressive approach may be expected to be deleterious for tolerability reasons or lack of options.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 it