Hepatic steatosis is highly prevalent across the paediatric age spectrum, including in pre‐school age children
Bibliographic record
Abstract
BACKGROUND: The prevalence of non-alcoholic fatty liver disease (NAFLD) in children is 8% in the general population, and 34% in the context of obesity. There is a paucity of data on the prevalence of hepatic steatosis in healthy children in Ontario. AIMS: To determine the prevalence of hepatic steatosis using abdominal computed tomography (CT) scans in a cohort of previously healthy children across the paediatric age spectrum in Ontario, Canada, and to determine any association between measures of abdominal adiposity and hepatic steatosis. METHODS: Retrospective review of the SickKids Trauma Database from 2004-2015. Previously healthy children ages 1-17 years having undergone an abdominal CT scan as a part of routine trauma assessment were included, and those with an intra-abdominal injury excluded. Steatosis was defined as a difference between liver and spleen attenuation ≤-25HU. The percentage of the total area occupied by abdominal subcutaneous adipose and visceral adipose tissue was measured. Anthropometrics and baseline demographics were collected. RESULTS: A total of 503 (51% male) children with mean (±SD) age 9.5 ± 4.5 years and weight z-score of 0.37 ± 1.05 were studied. Seventy-seven (15%, 95% CI [12%-18%]) had hepatic steatosis; no differences found between sexes or across age quartiles. The abdominal subcutaneous adipose tissue area was greater in those with hepatic steatosis compared to those without (32% [22-42] vs 24% [17-36], P = 0.003). The visceral adipose tissue area was significantly greater in older children ≥9.8 years with hepatic steatosis (7.7% [5.1-10] vs 6.6% (4.9-8.5), P = 0.04). CONCLUSION: Hepatic steatosis was highly prevalent in previously healthy children in Ontario, including children of pre-school age. We found an association between hepatic steatosis and abdominal subcutaneous adipose tissue, and in older children with visceral adipose tissue.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".