Tuberculous drug-induced liver injury and treatment re-challenge in Human Immunodeficiency Virus co-infection
Bibliographic record
Abstract
BACKGROUND: Tuberculosis drug-induced liver injury (TB-DILI) is the most common adverse event necessitating therapy interruption. The optimal re-challenge strategy for antituberculous therapy (ATT) remains unclear, especially in human immunodeficiency virus (HIV) co-infected individuals in high-prevalence settings such as South Africa. OBJECTIVE: To determine the incidence of and risk factors for the recurrence of TB-DILI with different ATT re-challenge strategies. MATERIALS AND METHODS: We conducted a retrospective chart review of patients managed for TB-DILI from 2005 to 2013 at King Edward VIII Hospital in Durban, South Africa. Relevant clinical and laboratory data at the presentation of TB-DILI, time to recovery of liver function, method of ATT re-challenge and outcome of re-challenge were documented. RESULTS: 1016 charts were reviewed, and 53 individuals with TB-DILI (48 HIV-co-infected) were identified. Following discontinuation of ATT, the median time to alanine aminotransferase normalization was 28 days (interquartile range 13-43). Forty-two subjects were re-challenged (30 regimen re-challenges and 12 step-wise re-challenges). 5 (12%) cases of recurrent TB-DILI were noted. Recurrences were not associated with the method of re-challenge. CONCLUSION: Based on the data available, it appears that full ATT can be safely restarted in the majority of subjects with a recurrence of DILI occurring in about 12% of subjects. The method of re-challenge did not appear to impact on the risk of recurrence. Ideally, a prospective randomized trial is needed to determine the best method of re-challenge.
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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 | 0.000 |
| 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".