Global Burden of Major Chronic Liver Diseases in 2021
Bibliographic record
Abstract
BACKGROUND: This study utilised the Global Burden of Disease data (2010-2021) to analyse the rates and trends in point prevalence, annual incidence and years lived with disability (YLDs) for major chronic liver diseases, such as hepatitis B, hepatitis C, metabolic dysfunction-associated liver disease, cirrhosis and other chronic liver diseases. METHODS: Age-standardised rates per 100,000 population for prevalence, annual incidence and YLDs were compared across regions and countries, as well as the socio-demographic index (SDI). Trends were expressed as percentage changes (PC) and estimates were reported with uncertainty intervals (UI). RESULTS: Globally, in 2021, the age-standardised rates per 100,000 population for the prevalence of hepatitis B, hepatitis C, MASLD and cirrhosis and other chronic liver diseases were 3583.6 (95%UI 3293.6-3887.7), 1717.8 (1385.5-2075.3), 15018.1 (13756.5-16361.4) and 20302.6 (18845.2-21791.9) respectively. From 2010 to 2021, the PC in age-standardised prevalence rates were-20.4% for hepatitis B, -5.1% for hepatitis C, +11.2% for MASLD and + 2.6% for cirrhosis and other chronic liver diseases. Over the same period, the PC in age-standardized incidence rates were -24.7%, -6.8%, +3.2%, and +3.0%, respectively. Generally, negative associations, but with fluctuations, were found between age-standardised prevalence rates for hepatitis B, hepatitis C, cirrhosis and other chronic liver diseases and the SDI at a global level. However, MASLD prevalence peaked at moderate SDI levels. CONCLUSIONS: The global burden of chronic liver diseases remains substantial. Hepatitis B and C have decreased in prevalence and incidence in the last decade, while MASLD, cirrhosis and other chronic liver diseases have increased, necessitating targeted public health strategies and resource allocation.
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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) | 0.000 | 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) | 0.005 | 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".