Fecal Microbiota Transplantation in Human Immunodeficiency Virus-Infected Patient Population: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Patients with human immunodeficiency virus (HIV) infection suffer from alterations in gut microbiota due to recurrent gastrointestinal infections and systemic inflammation. Fecal microbiota transplantation (FMT) appears to be a potential therapy; however, there are concerns about its safety. Likewise, no previous meta-analysis evaluated FMT efficacy in HIV-infected patients. Methods: We conducted a thorough electronic search on PubMed, Scopus, OVID, Web of Science, and Cochrane CENTRAL for clinical studies assessing the safety and efficacy of FMT in patients with HIV and gastrointestinal dysbiosis, where FMT was indicated to restore the disrupted microbiota. Results: and reduced the risk of gastrointestinal infections in HIV patients receiving antiretroviral therapy (odds ratio (OR) = 0.774, 95% confidence interval (CI): (0.62, 0.966)). Furthermore, adverse events, such as distention and bloating, associated with FMT were comparable between HIV and health controls (OR = 0.60, 95% CI: (0.07, 4.6)), with no statistical difference. Conclusions: Current evidence demonstrated that FMT is safe and effective in HIV patients suffering from alterations in gut microbiota. We recommend further multi-centric clinical studies to address the optimal transplant amount and source for FMT. To the best of our knowledge, this is the first meta-analysis to assess the safety and efficacy of FMT in patients with HIV.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.024 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".