A291 ANA-NEGATIVE AUTOIMMUNE HEPATITIS IN A 30-YEAR-OLD FEMALE: A DIAGNOSTIC CHALLENGE
Bibliographic record
Abstract
Abstract Background Autoimmune Hepatitis (AIH) is a chronic liver condition arising from the immune system's attack on liver cells. Its diagnosis is typically supported by the presence of autoantibodies, notably ANA. However, cases have been identified where AIH occurs in the absence of these conventional serologic markers. Prior studies have reported that ANA-negative AIH patients showed more acute presentations and higher frequencies of histologic acute hepatitis compared to those with positive autoimmune serology. As such, ANA-negative subset of patients presents a diagnostic challenge but highlights the evolving understanding of autoimmune processes in liver diseases. Aims To detail the clinical presentation, investigative measures, and treatment approach in a an otherwise healthy 30-year-old female diagnosed with ANA-negative autoimmune hepatitis. Methods The diagnostic approach included clinical symptomatology, biochemical tests, imaging via abdominal ultrasound, and histopathological evidence from an ultrasound-guided liver biopsy Results The patient presented initially with epigastric pain, jaundice, and pruritus over two weeks. Blood tests revealed acute hepatitis: ALT at 2723 U/L[JA1] , AST at 1428 U/L, and hyperbilirubinemia at 503 μmol/L, with GGT and ALP remaining normal. An abdominal ultrasound presented a typical liver morphology and biliary system. Initial autoimmune liver disease panels, including ANA, and viral hepatitis screenings, returned negative results. Furthermore, the patient's medication and drug history provided no additional clues for drug-induced aetiologies. For more conclusive diagnostics, an US-guided liver biopsy was performed during the admission revealing moderate acute hepatitis characterized by both interface hepatitis and lobular inflammation, prompting the suspicion for ANA-negative AIH. Initiating prednisone treatment (40 mg daily) based on clinical and biopsy evidence led to a significant reduction in liver enzymes and bilirubin. By the time of her discharge, her primary residual symptoms were mildly controlled jaundice and pruritus. She was transitioned to a tapering dose of prednisone, and Azathioprine was later added to her regimen. Subsequent close follow up revealed complete resolution of her symptoms. Notably, a 7-month follow-up unveiled a previously undetected AIH marker: ASMA with a titre of 1:80. Conclusions ANA-negative AIH, as showcased in this case, emphasizes the importance of a thorough and iterative diagnostic approach. Traditional serological markers may not always be present, necessitating reliance on a combination of clinical presentations and histopathology. Regular follow-ups and periodic re-evaluations are essential. This approach is crucial for pinpointing the diagnosis, guiding effective therapeutic interventions, and ultimately ensuring positive outcomes for patients navigating complex autoimmune liver conditions. Funding Agencies None
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".