A randomized trial of the impact of multiple micronutrient supplementation on mortality among HIV-infected individuals living in Bangkok
Bibliographic record
Abstract
OBJECTIVES: To examine the impact of high-dose multiple micronutrient supplementation on survival and disease progression among HIV-infected individuals in Thailand. DESIGN: Randomized placebo-controlled trial. METHODS: Four-hundred and eighty-one HIV-infected men and women living in and around Bangkok with CD4 cell counts in the range 50 x 10(6)- 550 x 10(6)/l were randomized to receive micronutrients or placebo for a period of 48 weeks. Trial participants were examined clinically 12-weekly and tested for CD4 cell count 24-weekly. A subset were tested for HIV plasma viral load at 48 weeks. RESULTS: Seventy-nine (16%) trial participants were lost to follow-up and 23 (5%) died. The death rate was lower in the micronutrients arm with the mortality hazard ratios [95% confidence interval (CI)] of 0.53 (0.22-1.25; P = 0.1) overall and 0.37 (0.13-1.06; P = 0.052) and 0.26 (0.07-0.97; P = 0.03) among those with CD4 cell counts < 200 x 10(6)/l and < 100 x 10(6)/l respectively. There was no impact on CD4 cell count or plasma viral load. CONCLUSIONS: Multiple micronutrient supplementation may enhance the survival of HIV-infected individuals with CD4 cell counts < 200 x 10(6)/l. This could have important public health implications in the developing world where access to antiretrovirals remains poor. The clinical findings need to be reproduced in other settings and the mechanism, which appears to be independent of change in CD4 cell count, merits further investigation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".