What Is the Likelihood That My Patient With Chronic Hepatitis C Will Develop Cirrhosis, Hepatocellular Carcinoma, and/or Hepatic Decompensation?
Bibliographic record
Abstract
Approximately 4 million persons within the United States are infected with the hepatitis C virus (HCV). Chronic HCV is the most common cause of cirrhosis and hepatocellular carcinoma (HCC), and over 40% of all patients who undergo liver transplantation in the United States, Europe, Canada, Australia, and many countries have chronic HCV infection. 1 Despite this, the natural history of chronic HCV has a wide spectrum. Only 4% of persons with chronic HCV develop end-stage liver disease and/or HCC and need to consider liver transplantation as a therapeutic option ( Figure 1-1 ). To some this may not sound like a major health problem. However, with 4 million persons infected, it is anticipated that 160,000 persons will develop end-stage disease and need to consider liver transplantation within the next 1 to 2 decades. Unfortunately, only about 5000 to 6000 liver transplants are performed in the United States annually, and roughly half of these are in patients without chronic HCV. It would therefore require 50 to 65 years for all those patients with end-stage liver disease from chronic HCV to receive a liver transplant. Clearly, this is an impossible task and many of these patients will not survive the pretransplant waiting period.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.021 |
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".