Detection of anti-isoniazid and anti–cytochrome P450 antibodies in patients with isoniazid-induced liver failure
Bibliographic record
Abstract
UNLABELLED: Isoniazid (INH)-induced hepatotoxicity remains one of the most common causes of drug-induced idiosyncratic liver injury and liver failure. This form of liver injury is not believed to be immune-mediated because it is not usually associated with fever or rash, does not recur more rapidly on rechallenge, and previous studies have failed to identify anti-INH antibodies (Abs). In this study, we found Abs present in sera of 15 of 19 cases of INH-induced liver failure. Anti-INH Abs were present in 8 sera; 11 had anti-cytochrome P450 (CYP)2E1 Abs, 14 had Abs against CYP2E1 modified by INH, 14 had anti-CYP3A4 antibodies, and 10 had anti-CYP2C9 Abs. INH was found to form covalent adducts with CYP2E1, CYP3A4, and CYP2C9. None of these Abs were detected in sera from INH-treated controls without significant liver injury. The presence of a range of antidrug and autoAbs has been observed in other drug-induced liver injury that is presumed to be immune mediated. CONCLUSION: These data provide strong evidence that INH induces an immune response that causes INH-induced liver injury.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".