The burden of cirrhosis and other chronic liver disease in the middle east and North Africa (MENA) region over three decades
Bibliographic record
Abstract
BACKGROUND: Cirrhosis comprises a significant health challenge in the Middle East and North African (MENA) region impacting healthcare systems and communities. This study sought to investigate trends in the burden of cirrhosis and other chronic liver disease, different etiologies, deaths, and the disability burden utilizing data from the Global Burden of Disease (GBD) database. METHODS: Analyzing epidemiological trends from 1990 to 2021 across 21 MENA countries, this research utilized data on age-standardized incidence rates (ASIR), age-standardized death rates, and age-standardized disability-adjusted life years (DALYs) to evaluate the burden of cirrhosis and other chronic liver disease. The study also examined national variations and sociodemographic relationships. RESULTS: The study identified a 114.9% increase in cirrhosis and other chronic liver disease incidence within the MENA region between 1990 and 2021, with 7,344,030 incident cases reported in 2021. The ASIR showed a steeper rise in females (9.6%) compared to males (7.0%). Etiology-specific analysis revealed an increase in the ASIR for MASLD related cirrhosis and other chronic liver disease by 22.2%, while those due to alcohol as well as hepatitis B and C decreased by 28.1%, 59.3%, and 30%, respectively. Despite the rising incidence, overall age-standardized death rates across all etiologies decreased by 54.3%, with DALYs showing a 51.4% decrease during the same period. Country-specific trends varied significantly, with Oman recording the highest annual ASIR increase (0.64%), and Qatar observing the most substantial annual reduction in age-standardized death rates (-2.88%). CONCLUSION: The study highlights evolving trends in cirrhosis and other chronic liver disease within the MENA region, emphasizing the necessity for comprehensive, etiology, and gender-specific interventions. Despite an increasing incidence, the observed improvements in mortality rates and age-standardized disability burden indicate progress in public health efforts to mitigate cirrhosis's impact. These findings point to the complex nature of cirrhosis outcomes and the urgent need for tailored strategies to manage its increasing burden effectively.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".