The Impact of HIV Status on Anti-tuberculous Therapy: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The global health challenge of tuberculosis (TB) and human immunodeficiency virus (HIV) co-infection demands an in-depthevaluation of TB treatment's safety and efficacy in individuals, regardless of their HIV status.Objective: This study critically examines the literature to determine the effectiveness of anti-TB therapies among HIV-positive and HIV-negativepatients.Methods: We conducted a systematic review of the literature by searching databases such as Web of Science, SCOPUS, PubMed, and the CochraneCentral Register up to 30 August 2023. Using RAYYAN.AI for initial screening and the R programming language for meta-analysis, we extractedand analysed outcome data, focusing on treatment success and mortality rates. The analysis included heterogeneity assessment via the I² test and biasrisk evaluation via the Newcastle-Ottawa Scale.
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How this classification was reachedexpand
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".