Metabolic syndrome and liver steatosis occur at lower body mass index in US Asian patients with chronic hepatitis B
Bibliographic record
Abstract
We have previously shown that ultrasound identifies significant steatosis in patients with chronic HBV (CHB). However, the relationship between CHB, metabolic syndrome (MS) and steatosis is poorly understood. In this tertiary care, single-centre retrospective cohort study of 617 CHB patients, we examined the prevalence of MS and steatosis in a predominantly Asian US cohort. Patients were predominantly male (57%) with a mean age of 53 years, Asian (88%), on HBV therapy (64%) and had undetectable DNA (65%). 21% had MS, of which hypertension (41%), dyslipidemia (41%) and obesity (32%) were most common. Patients with MS were more likely to be older (60 vs 52 [P < 0.001]), have steatosis (40% vs 17% [P < 0.001]) and have a higher ALT (29 vs 25 [P = 0.003]). Of the 22% of patients with steatosis by ultrasound, a higher prevalence of MS (38% vs 16% [P < 0.001]) and higher ALT (31 vs 24 [P < 0.001]) was observed. Asian patients had a lower BMI than non-Asians (mean 24 vs 26 [P = 0.001]) but similar prevalence of MS risk factors and steatosis. Asian patients with a BMI between 25 and 30 and two other MS risk factors had steatosis at the same rate as patients with a BMI > 30 and at least two other MS risk factors. We found a strong association between MS, steatosis and elevated ALT in HBV patients. Asian HBV patients have lower BMI than non-Asians yet have the same prevalence of steatosis and other MS risk factors, supporting guidelines for lower BMI targets in Asians.
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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 | 0.000 | 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) | 0.001 | 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".