Kratom-Induced Cholestatic Liver Injury Mimicking Anti-Mitochondrial Antibody-Negative Primary Biliary Cholangitis: A Case Report and Review of Literature
Bibliographic record
Abstract
Kratom is an herbal supplement used to relieve chronic pain or opioid withdrawal symptoms. Recent news articles covering adverse effects associated with kratom use have brought attention to its organ toxicities. Reports of kratom-induced hepatic toxicity are limited and only three case reports of kratom-induced liver injury with histopathologic examination of the liver biopsies are available. A 40-year-old female presented with symptoms of mixed cholestatic and hepatocellular liver injury without clear etiology. The laboratory and imaging workup suggested possibilities of autoimmune hepatitis, autoimmune hepatitis-primary biliary cholangitis (PBC) overlap syndrome, or drug-induced liver injury. Autoantibodies including anti-mitochondrial antibody (AMA) were negative. Liver biopsy showed granulomatous hepatitis with prominent duct injury, suggestive of AMA-negative PBC. She subsequently was referred to a hepatologist and a history of recent kratom use was finally revealed. Kratom was discontinued and the symptoms improved. Kratom-induced hepatic toxicity may manifest with variable biochemical and clinical abnormalities. Histologically, it may mimic AMA-negative PBC. Our case highlights the importance of thorough history taking, interdisciplinary approach and communication for optimal patient care.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".