A Case of Advanced Hepatocellular Carcinoma Without Cirrhosis History
Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) is one of the most common sequelae of liver disease, and it is the fourth leading cause of cancer worldwide. This disease often arises from cirrhosis and chronic liver disease such as fatty liver disease or autoimmune hepatitis. HCC has particular prevalence in developed countries where metabolic issues such as diabetes and obesity are common. Males and elderly patients are predominantly affected compared to females and young people, respectively. Lastly, patient presentations of HCC can vary depending on staging, cirrhosis state, and current symptoms. Diagnosis of HCC is uniquely defined with ultrasound, CT, and MRI. HCC demonstrates a distinctive arterial phase hyperenhancement and portal venous washout on contrast CT, which differentiates it from other liver masses and allows for accurate diagnosis without invasive biopsy. Additionally, an AFP level above $400 \mathrm{ng} / \mathrm{mL}$ can assist with HCC screening and diagnosis. The management of HCC involves many avenues of care involving tumor characterization, liver function and compensation, and patient symptoms and preferences. Depending on patient status and disease progression, treatments may include surgical resection, liver transplantation, and systemic therapies. In this case report, we have a 77-year-old female without a history of cirrhosis developing advanced HCC. After presenting to the ED with jaundice and altered consciousness, she was diagnosed with HCC via contrastenhanced CT. This is a case with an atypical presentation of HCC in a previously non-cirrhotic liver. Therefore, the role of CT in diagnosing HCC is pivotal for timely management, averting the need to wait for biopsy results. This patient presented with a profile of HCC that precluded traditional therapeutic interventions such as surgical resection, liver transplant, or chemotherapy, suggesting the consideration for palliative care. Furthermore, this case highlights age as a significant risk factor and highlights the importance of comprehensive screening in at-risk populations to improve early detection and patient outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".