Case Report and Literature Review: Quinacrine-induced Cholestatic Hepatitis in Undifferentiated Connective Tissue Disease
Bibliographic record
Abstract
To the Editor: A 45-year-old African American woman presented to the rheumatology clinic with a history of undifferentiated connective tissue disease (UCTD), manifesting as biopsy-proven urticarial dermatitis, inflammatory arthritis, fatigue, and weight loss in the setting of positive immunofluorescence antinuclear antibodies (1:160, speckled pattern), anti-RNP, anti-Sm/RNP, and antichromatin antibodies. She started treatment with quinacrine 100 mg per day for her disease. Quinacrine was chosen because she developed a pruritic rash after taking hydroxychloroquine for 2 months. At the time she started treatment with quinacrine, she was also receiving 5 mg of prednisone, diphenhydramine as needed, ergocalciferol, and norgestimate-ethinyl estradiol. All of these were longterm medications. Four weeks after starting quinacrine, she presented to the emergency department with generalized fatigue, loss of appetite, nausea, diffuse abdominal pain, scleral icterus, and dark tea-colored urine. She reported no history of new medications, supplements, or alcohol intake. Laboratory investigations demonstrated … Address correspondence to Dr. R. Namas, Department of Internal Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, Michigan 48109, USA. E-mail: rnamas{at}med.umich.edu
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".