Non-alcoholic fatty liver disease: relation to juvenile obesity, lipid profile, and hepatic enzymes
Bibliographic record
Abstract
The prevalence of juvenile obesity is increasing, reaching epidemic proportions, presenting a link not only to NAFLD (non-alcoholic fatty liver disease) but to abnormal lipid profiles and liver enzyme abnormalities. Liver ultrasonography is a sensitive and specific tool for the recognition of NAFLD. This study aims to assess the association between NAFLD and juvenile obesity and to determine the other related changes in a set of indicators, including lipid profile abnormalities and serum transaminases. The sample included 470 obese and 210 non-obese individuals aged 6-16. Anthropometric measures were assessed, with the serum lipid profile and liver transaminases, and abdominal ultrasonography was used to detect NAFLD. Fatty liver was found in 38% of the obese subjects and none of the non-obese subjects. Within obese subjects, mean body mass index (BMI) and waist circumference increased significantly in patients with NAFLD compared to those without fatty liver. Moreover, LDL (low-density lipoprotein), CHOL (cholesterol), and serum liver enzymes were significantly higher in the presence of NAFLD. In conclusion, NAFLD commonly associates with juvenile obesity, relating to obesity and the abnormal lipid profile (including elevated CHOL and LDL) among obese people, reflecting elevated liver transaminases, which increase the risk of cirrhosis.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".