Total Bilirubin Levels in Nonalcoholic Fatty Liver Disease and All- cause and Cause-specific Mortality in US Adults
Bibliographic record
Abstract
BACKGROUND AND AIMS: Nonalcoholic Fatty Liver Disease (NAFLD) is a chronic progressive illness with a spectrum of disease severity from steatosis to end-stage liver disease. Emerging evidence suggests total serum bilirubin levels are inversely related to the prevalence of metabolic syndrome including NAFLD. We investigated the effects of bilirubin on all-cause and cause-specific mortality stratified by NAFLD status. METHODS: We used the third National Health and Nutrition Examination Survey Cohort (1988-1994) and linked mortality dataset through 2019. Cox-regression models were constructed to assess the association between bilirubin levels categorized by quartile with all-cause and cause-specific mortality. RESULTS: During the median follow-up of 324 months (n=11,078), higher bilirubin levels were associated with a reduction in risk of all-cause mortality in the multivariate model (hazard ratio [HR]: 0.83, 95% confidence interval [CI]: 0.71-0.97 for quarter 4 [highest bilirubin levels] vs. quarter 1 [lowest bilirubin levels], p for trend=0.033). Higher bilirubin levels were associated with a lower risk for all-cause mortality in individuals with NAFLD (HR; 0.68, 95% CI: 0.55-0.86 for quarter 4, p for trend=0.010); however, this protective association with higher bilirubin levels was not noted in those without NAFLD. Higher bilirubin levels were associated with a lower risk for cardiovascular and cancer-related mortality in individuals with NAFLD. CONCLUSIONS: In this large nationally representative sample of American adults, higher bilirubin levels in NAFLD were associated with a lower risk of all-cause mortality, which may be derived from a lower risk of cardiovascular/cancer-related mortality.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".