Baseline Naive CD4+ T-cell Level Predicting Immune Reconstitution in Treated HIV-infected Late Presenters
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Bibliographic record
Abstract
BACKGROUND: Among HIV-infected patients initiating antiretroviral therapy (ART), early changes in CD4+ T-cell subsets are well described. However, HIV-infected late presenters initiating treatment present with a suboptimal CD4+ T-cell reconstitution and remain at a higher risk for AIDS and non-AIDS events. Therefore, factors associated with CD4+ T-cell reconstitution need to be determined in this population, which will allow designing effective immunotherapeutic strategies. METHODS: Thirty-one adult patients with baseline CD4+ T-cell count <350 cells/mm3 exhibiting viral suppression after ART initiation were followed in the HIV/AIDS research center of Peking Union Medical College Hospital in Beijing, China, from October 2002 to September 2013. Changes in T-cell subsets and associated determinants were measured. RESULTS: Median baseline CD4+ T-cell count was 70 cells/mm3. We found a biphasic reconstitution of T-cell subsets and immune activation: a rapid change during the first 6 months followed by a more gradual change over the subsequent 8 years. Baseline CD4+ T-cell count >200 cells/mm3 in comparison to CD4+ T-cell count ≤200 cells/mm3 was associated with more complete immune Reconstitution (77.8% vs. 27.3% respectively; P = 0.017) and normalized CD4/CD8 ratio. We showed that the baseline percentage of naive CD4+ T-cell was a predictive marker for complete immune reconstitution (area under receiver operating characteristic curve 0.907), and 12.4% as cutoff value had a sensitivity of 84.6% and a specificity of 88.2%. CONCLUSIONS: Baseline naive CD4+ T-cell percentage may serve as a predictive marker for optimal immune reconstitution during long-term therapy. Such study findings suggest that increasing thymic output should represent an avenue to improve patients who are diagnosed late in the course of infection.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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