The relative expression of hepatocellular and cholestatic liver enzymes in adult patients with liver disease
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVES: Hepatocellular liver injury is characterized by elevations in serum alanine (ALT) and aspartate (AST) aminotransferases while cholestasis is associated with elevated serum alkaline phosphatase (ALP) levels. When both sets of enzymes are elevated, distinguishing between the two patterns of liver disease can be difficult. The aim of this study was to document the predicted ranges of serum ALP values in patients with hepatocellular liver injury and ALT or AST values in patients with cholestasis. MATERIALS AND METHODS: Liver enzyme levels were documented in adult patients with various types and degrees of hepatocellular (non-alcoholic fatty liver disease, hepatitis B and C, alcohol and autoimmune hepatitis) and cholestatic (primary biliary cholangitis and primary sclerosing cholangitis) disease. RESULTS: In 5167 hepatocellular disease patients with ALT (or AST) values that were normal, 1-5×, 5-10× or >10× elevated, median (95% CI) serum ALP levels were 0.64 (0.62-0.66), 0.72 (0.71-0.73), 0.80 (0.77-0.82) and 1.15 (1.0-1.22) fold elevated respectively. In 252 cholestatic patients with ALP values that were normal, 1-5× or >5× elevated, serum ALT (or AST) values were 1.13 (0.93-1.63), 2.47 (2.13-2.70) and 4.57 (3.27-5.63) fold elevated respectively. In 56 patients with concurrent diseases, ALP levels were beyond predicted values for their hepatitis in 38 (68%) and ALT (or AST) values beyond predicted values for their cholestatic disorder in 24 (43%). CONCLUSIONS: These data provide health care providers with predicted ranges of liver enzymes in patients with hepatocellular or cholestatic liver disease and may thereby help to identify patients with concurrent forms of liver disease.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".