Association of N-acetyltransferase-2 Polymorphism with AntituberculosisInduced Hepatotoxicity: A Meta-analysis
Bibliographic record
Abstract
Background: N-acetyltransferase (NAT2) polymorphisms were reported to play important roles in antituberculosis-induced hepatotoxicity (ATDIH). However, the allelic types with increased risks for ATDIH were inconsistent as most studies are of a small sample size. Objective: The objective of the study was to conduct a meta-analysis to identify NAT2 alleles associated with increased risks of ATDIH. Methods: Studies reported on NAT2 polymorphism with the risk of ATDIH were searched systematically in PubMed, Scopus, and the World of Sciences. Studies were included if they fulfilled the inclusion criteria and excluded accordingly. Quality assessments were done using Newcastle-Ottawa Score. Statistical analysis was performed using Review Manager version 5.3. Cochrane Q-statistic test and I2 statistic were used to assess and quantify heterogeneity. Results: A total of 12 studies involving 580 cases and 3129 controls were included. NAT2 polymorphism was significantly associated with the risk of ATDIH with an odd ratio (OR) of 2.76 (1.86 – 4.10, 95% CI). Among the slow acetylators genotypes, NAT2*5/*7 carry the highest risk associated with ATDIH. Conclusion: NAT2 polymorphism was significantly associated with ATDIH.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.043 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".