A clinically relevant method to screen for hepatic steatosis in overweight adolescents: a cross sectional study
Bibliographic record
Abstract
BACKGROUND: To develop a screening algorithm to detect hepatic steatosis in overweight and obese adolescents. METHODS: We performed a cross sectional study of 129 overweight adolescents 13-18 yrs. The primary outcome, hepatic steatosis was defined as an intracellular triglyceride content > 5.5 mg/g and quantified using (1)H-magenetic resonance spectroscopy. Primary predictor variables included, alanine and aspartate transaminases (ALT/AST) and features of the metabolic syndrome. RESULTS: Hepatic steatosis was present in 33% of overweight and obese adolescents. Adolescents with hepatic steatosis were more likely to be boys (adjusted OR: 4.8; 95% CI: 2.5-10.5), display a higher waist circumference (111 ± 12 vs 100 ± 13 cm, p < 0.001) and have metabolic syndrome (adjusted OR: 5.1; 95% CI: 1.6-16.4). Serum ALT predicted hepatic steatosis in boys (AUC: 0.82; 95% CI: 0.70-0.95; p < 0.001) but not girls (AUC = 0.63; 95% CI: 0.46-0.75, p = 0.16). An ALT >20 U/L, combined with the presence of metabolic syndrome, male gender and an elevated waist circumference provided the best model (AUC 0.85) with high sensitivity (72%) and specificity (82%) and positive and negative predictive values of 61% and 89% respectively. CONCLUSIONS: Serum transaminases provide modest predictive value for hepatic steatosis in youth. The ALT threshold for predicting hepatic steatosis is significantly lower than current clinical thresholds for predicting non-alcoholic fatty liver disease. The addition of ALT, presence of the metabolic syndrome and male gender significant improve the ability to predict hepatic steatosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".