The effect of Chinese medicine therapeutics on HIV/AIDS: a systematic review and network meta-analysis
Bibliographic record
Abstract
Background Although antiretroviral therapy (ART) effectively suppresses HIV, incomplete immune reconstitution affects 20%–30% of adherent patients. Chinese Medicine (CM) demonstrates potential as a complementary therapy for human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), yet its long-term impact on immune recovery remains unestablished. This network meta-analysis (NMA) aimed to compare CM interventions for enhancing CD4 + T-cell counts and overall efficacy in HIV/AIDS management. Methods We systematically searched PubMed, Embase, Web of Science, and the Cochrane Library from inception to 27 August 2024 for randomized controlled trials (RCTs) and observational studies on CM for HIV/AIDS. Bayesian NMA was conducted using R 4.2.2 with BUGSnet 1.1.0 package. Surface under cumulative ranking (SUCRA) probabilities ranked interventions. Risk of bias was assessed with Cochrane ROB 2.0 for RCTs and Newcastle-Ottawa Scale for observational studies (PROSPERO: CRD42024560340). Results A total of 34 studies ( n = 8,933 participants) evaluating 16 interventions were included. Key findings: For CD4 + restoration, Chinese herbal formulae plus ART significantly outperformed ART alone (MD = 163 cells/μL, 95% Bayesian credible interval [CrI]: 3.93–326.46), ranking first (SUCRA = 0.92). Single herbs plus ART ranked second for CD4 + recovery (MD = 178.54, 95% CrI: −188.57–553.24; SUCRA = 0.85). In overall treatment efficacy (survival/quality of life), Chinese herbal formulae plus Western medical therapy demonstrated the highest SUCRA (0.96). Conclusion CM-ART combinations—particularly Chinese herbal formulae with ART—optimize immune reconstitution in HIV/AIDS. Chinese herbal formulae plus ART represents the most effective CD4 + restoration strategy. These findings support integrating evidence-based CM into HIV care, but pharmacokinetic interactions and long-term safety require validation through multicenter trials. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024560340 , PROSPERO CRD42024560340.
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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 | 0.020 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.043 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".