Effect of Micronutrient and Probiotic Fortified Yogurt on Immune-Function of Anti-Retroviral Therapy Naive HIV Patients
Bibliographic record
Abstract
BACKGROUND: Micronutrient supplementation has been shown to reduce the progression of HIV but does not have an effect on the intestinal barrier or the intestinal microbiota of HIV patients. Studies have suggested that probiotics could potentially complement micronutrients in preserving the immune-function of HIV patients. OBJECTIVE: Assess the impact of micronutrient supplemented probiotic yogurt on the immune function of HIV patients. DESIGN: We performed a randomized, double blind, controlled trial with CD4 count as primary outcome among HIV patients naïve to anti-retroviral treatment. Secondary outcomes included hematological parameters, incidence of diarrhea and clinical symptoms. A total of 112 HIV patients were randomized to receive a micronutrient fortified yogurt with (n = 55) or without additional probiotic Lactobacillus rhamnosus GR-1 (n = 57) for four weeks. RESULTS: An average decline in CD4 count of -70 cells/μL (95% CI: -154 to -15) was observed in the micronutrient, probiotic group versus a decrease of -63 cells/μL (95% CI: -157 to -30) in the micronutrient control group (p = 0.9). Additional probiotic supplementation was well tolerated and not associated with adverse events. No difference between groups was detected in incidence of diarrhea or clinical symptoms. An improvement of hemoglobin levels was observed for all subjects, based upon a mean difference from baseline of 1.4 g/L (SD = 6) (p = 0.02). CONCLUSION: The addition of probiotics to a micronutrient fortified yogurt was well tolerated by HIV patients but was not associated with a further increase in CD4 count after one month.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".