Hepatotoxicity and tuberculosis treatment outcomes in chronic liver disease
Bibliographic record
Abstract
Background: The treatment of tuberculosis (TB) is known to cause liver injury, however, there is limited data to guide optimal treatment for patients with chronic liver disease. Methods: We undertook a retrospective case series of patients with chronic liver disease and TB disease. The primary objective was to determine if there was a difference in the incidence of drug-induced liver injury (DILI) in patients with cirrhosis versus those with chronic hepatitis. Additionally, we sought to compare TB treatment outcomes, type and duration of therapy, and incidence of adverse events. Results: We included 56 patients (chronic hepatitis 40; cirrhosis 16). There were 33 patients (58.9%) who experienced DILI requiring treatment modification, with no significant difference between groups (65% versus 43.8%, p = 0.23). Patients with chronic hepatitis were more likely to receive treatment with standard first-line intensive phase therapy that included a combination of rifampin (RIF), isoniazid, and pyrazinamide (80.8% versus 19.2%, p = 0.03) and any regimen than included isoniazid (92.5% versus 68.8%, p = 0.04). The risk of DILI was higher when more hepatotoxic TB medications were used. Overall treatment success in this cohort was low (55.4%), with no significant difference between groups (62.5% versus 37.5%, p = 0.14). Most patients with treatment success (97%) were able to tolerate a rifamycin. Conclusions: The risk of DILI is high, especially with the use of isoniazid, in patients with TB and chronic liver disease. This risk can be effectively mitigated with no difference in treatment outcomes in the presence of cirrhosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".