Assessment of Metabolic Dysfunction-associated Steatotic Liver Disease and Liver Fibrosis: A Cross-sectional Study in Asymptomatic Individuals in Greater Vancouver
Bibliographic record
Abstract
Background and Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of hepatic fibrosis, yet its prevalence in asymptomatic populations remains unclear. This study aimed to assess the prevalence of steatosis and significant fibrosis in asymptomatic individuals without known liver disease in the Greater Vancouver Area. Methods: Interested individuals voluntarily registered online via the Canadian Liver Foundation website or by telephone. Inclusion criteria included age ≥ 19 years, no known liver disease, and low alcohol intake (<30 g/day for men, <20 g/day for women). Demographic and clinical data were collected, and all participants underwent transient elastography after a 3-h fast. The study aimed to collect 4,500 analyzable scans while reflecting the region's ethnic diversity. Results: A total of 4,193 participants were analyzed. The median age was 62 years, the median body mass index was 25.4, and 45% were male. Asian individuals comprised 42% of the cohort. Steatosis was present in 59.6% of participants, and 45.7% met diagnostic criteria for MASLD. Significant fibrosis (F2-F4) was found in 8.6%. Age, male sex, ethnicity, cardiac disease, diabetes, hypertension, and obesity were significantly associated with fibrosis. Logistic regression analysis confirmed age, weight, diabetes, dyslipidemia, hypertension, and obesity as independent predictors. Conclusions: A substantial proportion of asymptomatic individuals in Greater Vancouver have undetected MASLD and significant fibrosis. Early identification of high-risk groups may support broader implementation of transient elastography screening. This study provides one of the first North American population-based estimates of MASLD and fibrosis stratified by ethnicity, offering new insights into liver disease distribution among Caucasian, Chinese, and South Asian populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".