Association of the Nonalcoholic Hepatic Steatosis and Its Degrees With the Values of Liver Enzymes and Homeostasis Model Assessment-Insulin Resistance Index
Bibliographic record
Abstract
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is among the most common chronic diseases of the modern world with a wide variety of factors including genetic, environmental and metabolic. The aim of this study was to verify the association between the degrees of hepatic steatosis at the abdominal ultrasound and the values of aminotransferases (aspartate aminotransferase (AST) and alanine transferase (ALT)), gamma glutamyl transpeptidase (GGT) and homeostasis model assessment-insulin resistance (HOMA-IR) index. METHODS: A prospective, descriptive survey study, using a quantitative analytical examination, was conducted from July 2013 to July 2014. In the statistical analysis, values were expressed as median, first and third quartiles. We used the nonparametric Kruskal-Wallis test to compare the medians between the degrees of steatosis, adopted a statistical significance of 5% (P ≤ 0.05) and used the statistical program SPSS 22.0. RESULTS: We diagnosed 233/800 (29.1%) patients with hepatic steatosis on routine ultrasound, and 65.7% were female. Regarding degrees, 119 had grade 1 (51.0%), 94 grade 2 (40.4%) and 20 grade 3 (8.6%). The median age of the patients with grade 1, 2 or 3 did not vary significantly (P > 0.05). The median body mass index (BMI), although clinically important because of its elevation, did not differ significantly (P > 0.05). ALT levels increased as the degree of hepatic steatosis has advanced as well as the levels of AST, GGT and HOMA-IR. AST values showed a greater association with the severity of fatty liver (P = 0.0001) than the ALT (P = 0.001). CONCLUSIONS: ALT, AST, GGT and HOMA-IR are associated to the degrees of hepatic steatosis on ultrasound and can help in the selection of patients for the liver histological evaluation.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".