Efficacy, effectiveness, and safety of integrase inhibitors in the treatment of HIV/AIDS in patients with tuberculosis: A systematic review and meta-analysis
Bibliographic record
Abstract
Aims: To evaluate the efficacy, effectiveness, and safety of integrase inhibitors in the treatment of HIV/AIDS in patients coinfected with tuberculosis (TB). Methods: Clinical trials or observational studies were included. The searches were performed in the MEDLINE, EMBASE, LILACS, COCHRANE, Web of Science, Scopus, and CINAHL databases using the terms “HIV”, “AIDS”, “tuberculosis”, “raltegravir potassium”, “dolutegravir”, “elvitegravir”, “bictegravir”, “integrase inhibitor”, and their respective synonyms. The methodological quality of the studies was independently assessed using the Cochrane risk of bias and Newcastle Ottawa scales. Results: Reports from three randomised clinical trials and a historical cohort were included. Patients coinfected with TB and HIV/AIDS showed a good response to TB treatment, which was above 85% in all arms of the evaluated studies. As a primary outcome, the HIV viral load suppression rates at week 48 were greater than 60% in all arms. The therapies evaluated in patients coinfected with TB and HIV/AIDS were also proven to be safe. However, there was no statistically significant difference in the efficacy outcomes between the efavirenz and integrase inhibitor arms, and regarding safety outcomes, there were few events compared with the total. Furthermore, the certainty of the evidence of the outcomes assessed was low, indicating that future research is likely to have an important impact on this estimate. Conclusion: Integrase inhibitors are effective and well tolerated, being an alternative to efavirenz in clinical protocols. However, more studies with high quality evidence are needed on the use of this treatment in health systems.
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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 | 0.022 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.043 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".