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Record W4404353474 · doi:10.1016/j.jhepr.2024.101271

Global burden of metabolic dysfunction-associated steatotic liver disease, 2010 to 2021

2024· article· en· W4404353474 on OpenAlex
Gong Feng, Giovanni Targher, Christopher D. Byrne, Yusuf Yılmaz, Vincent Wai‐Sun Wong, Cosmas Rinaldi Adithya Lesmana, Leon A. Adams, Jérôme Boursier, George Papatheodoridis, Mohamed El‐Kassas, Nahúm Méndez‐Sánchez, Silvia Sookoian, Laurent Castéra, Wah‐Kheong Chan, Feng Ye, Sombat Treeprasertsuk, Helena Cortez‐Pinto, Hon Ho Yu, Won Kim, Manuel Romero‐Gómez, Atsushi Nakajima, Khin Maung Win, Seung Up Kim, Adriaan G. Holleboom, Giada Sebastiani, Ponsiano Ocama, John Ryan, Monica Lupșor‐Platon, Hasmik Ghazinyan, Mamun Al-Mahtab, Saeed Hamid, Nilanka Perera, Khalid Alswat, Qiuwei Pan, Michelle T. Long, Isakov Va, Man Mi, Marco Arrese, Arun J. Sanyal, Shiv Kumar Sarin, Nathalie C. Leite, Luca Valenti, Philip N. Newsome, Hannes Hagström, Salvatore Petta, Hannele Yki‐Järvinen, Jörn M. Schattenberg, Marlén Castellanos, Isabelle Leclercq, Gulnara Aghayeva, Abdel‐Naser Elzouki, Ali Tumi, Ala I. Sharara, Asma Labidi, Faisal M. Sanai, Khaled Matar‎, Maen Almattooq, Maisam Akroush, Mustapha Benazzouz, Nabil Debzi, Maryam Alkhatry, Salma Barakat, Said A. Al‐Busafi, John Rwegasha, Wah Yang, Adwoa Agyei‐Nkansah, Christopher Opio, Mohammadjavad Sotoudeheian, Yu Jun Wong, Jacob George, Ming‐Hua Zheng

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJHEP Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsRoyal Victoria HospitalUniversity of Alberta HospitalUniversity of AlbertaMcGill University Health CentreRoyal Victoria Regional Health Centre
FundersNatural Science Basic Research Program of Shaanxi ProvinceScientific Research Plan Projects of Shaanxi Education DepartmentCollege of Medicine, Seoul National UniversityAlnylam PharmaceuticalsAstraZenecaGenentechLG ChemIpsenNational Key Research and Development Program of ChinaSun PharmaKey Science and Technology Program of Shaanxi ProvinceSiemens HealthineersYakult Bio-Science FoundationIntercept PharmaceuticalsAssistance publique-Hôpitaux de ParisEducation Department of Shaanxi ProvinceUniversidade de LisboaUniversidad Nacional Autónoma de MéxicoFaculty of Medicine, Chulalongkorn UniversityNational and Kapodistrian University of AthensDaewoong Pharmaceutical CompanyUniversiti MalayaNovo NordiskHelwan UniversityYonsei UniversityEisaiNational Natural Science Foundation of ChinaPfizerConsejo Nacional de Investigaciones Científicas y TécnicasInstitut National de la Santé et de la Recherche MédicaleRoyal College of Surgeons in IrelandUniversidad de SevillaChulalongkorn UniversityMcGill University Health CentreRegeneron PharmaceuticalsBristol-Myers SquibbChinese University of Hong KongEli Lilly and CompanyCSL BehringYonsei University College of MedicineMcGill UniversityUniversitas IndonesiaAmsterdam University Medical CentersGilead SciencesSeoul National UniversityInventiva PharmaKowa CompanySanofi
KeywordsBurden of diseaseMedicineDiseaseLiver dysfunctionIntensive care medicineEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Background & Aims: This study used the Global Burden of Disease data (2010-2021) to analyze the rates and trends of point prevalence, annual incidence, and years lived with disability (YLDs) for metabolic dysfunction-associated steatotic liver disease (MASLD) in 204 countries. Methods: Total numbers and age-standardized rates per 100,000 population for MASLD prevalence, annual incidence, and YLDs were compared across regions and countries by age, sex, and sociodemographic index (SDI). Smoothing spline models were used to evaluate the relationship between the burden of MASLD and SDI. Estimates were reported with uncertainty intervals (UI). Results: 14,310.6 cases per 100,000 population). Prevalence peaked at ages 45-49 for men and 50-54 for women. Kuwait (32,312.2 cases per 100,000 people; 95% UI: 29,947.1-34,839.0), Egypt (31,668.8 cases per 100,000 people; 95% UI: 29,272.5-34,224.7), and Qatar (31,327.5 cases per 100,000 people; 95% UI: 29,078.5-33,790.9) had the highest prevalence rates in 2021. The largest increases in age-standardized point prevalence estimates from 2010 to 2021 were in China (16.9%, 95% UI 14.7%-18.9%), Sudan (13.3%, 95% UI 9.8%-16.7%) and India (13.2%, 95% UI 12.0%-14.4%). MASLD incidence varied with SDI, peaking at moderate SDI levels. Conclusions: MASLD is a global health concern, with the highest prevalence reported in Kuwait, Egypt, and Qatar. Raising awareness about risk factors and prevention is essential in every country, especially in China, Sudan and India, where disease incidence and prevalence are rapidly increasing. Impact and implications: This research provides a comprehensive analysis of the global burden of MASLD, highlighting its rising prevalence and incidence, particularly in countries with varying sociodemographic indices. The findings are significant for both clinicians and policymakers, as they offer critical insights into the regional disparities in MASLD burden, which can inform targeted prevention and intervention strategies. However, the study's reliance on modeling and available data suggests cautious interpretation, and further research is needed to validate these findings in clinical and real-world settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.264
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it