ArticleGastro hep advances2025
Discrepancy in Metabolic Dysfunction-Associated Steatotic Liver Disease Prevalence in a Large Northern California Cohort.
Article in Gastro hep advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Article
- A comprehensive narrative review of artificial intelligence use in the diagnosis and management of metabolic dysfunction-associated steatotic liver disease.Translational gastroenterology and hepatology · 2026Review
- Unrecognized Fibrosis Risk in MASLD: A Real-World Analysis and the Case for AI-Augmented Stratification.Gastro hep advances · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: The estimated prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) in US adults is 31.3%. However, little is known about MASLD diagnosis rates in clinical practice. We used data from electronic health records and assessed the annual MASLD prevalence. Methods: We conducted a repeated cross-sectional analysis of a retrospective dynamic cohort study among 2,040,688-2,852,060 Kaiser Permanente Northern California adult members without other chronic liver diseases from 2009 to 2018. Annual MASLD prevalence was identified based on International Classification of Diseases, Ninth or Tenth Revision, Clinical Modification diagnosis codes, the application of natural language processing of all radiology imaging report text that included the liver, and the application of the Dallas Steatosis Index, a MASLD prediction algorithm. Results: Between 2009 and 2018, the estimated MASLD prevalence ranged from 0.37% to 0.95% using diagnosis codes, 0.88%-1.37% using imaging, and 6.14%-11.27% using the Dallas Steatosis Index. Conclusion: Reliance on diagnosis codes or natural language processing on hepatic imaging, or the Dallas Steatosis Index, to identify MASLD patients within a large health-care system yields much lower than expected prevalence. These results underscore an underdiagnosis issue and highlight the need for improved diagnostic practices.
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Registered trials
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