Does MASLD phenotype based on body weight predict long-term all-cause mortality in patients following acute myocardial infarction?
5,702 patients following acute myocardial infarction (AMI)
Metabolic dysfunction-associated steatotic liver disease (MASLD) phenotypes based on body weight (obesity MASLD, non-obesity MASLD, obesity non-MASLD)
Non-obesity non-MASLD phenotype
Long-term all-cause mortalityhard clinical
Both obesity and non-obesity MASLD phenotypes independently predict long-term all-cause mortality following AMI, with the highest risk observed in the non-obesity MASLD group.
OBJECTIVE: Metabolic dysfunction-associated steatotic liver disease (MASLD) and obesity increases risk of cardiovascular disease. This cohort study examines the prognostic value of MASLD, across body weight categories, in a secondary preventative acute myocardial infarction (AMI) cohort. METHODS: Patients with AMI were stratified into four phenotypes-obesity MASLD, non-obesity MASLD, obesity non-MASLD, non-obesity non-MASLD. The primary outcome was all-cause mortality. Cox regression analysis was performed to investigate determinants of long-term all-cause mortality. RESULTS: Of 5702 patients, majority were in the non-obesity non-MASLD group (66.7%), followed by obesity MASLD (16.1%), non-obesity MASLD (11.2%) and non-obesity MASLD (6.0%). Across the four phenotypes, obesity MASLD had the highest cardiometabolic burden, followed by non-obesity MASLD. Non-obesity MASLD had the highest risk of heart failure (p = 0.034), cardiogenic shock (p < 0.001), and all-cause long-term mortality (p = 0.019). The non-obesity MASLD (HR 1.400, 95%CI 1.077-1.820, p = 0.012) and obesity MASLD phenotypes (HR 1.222, 95%CI 1.005-1.485, p = 0.044) were independently associated with long-term all-cause mortality. CONCLUSIONS: Obesity and non-obesity MASLD phenotypes were predictors of all-cause mortality following AMI, with an even larger magnitude of mortality risk in the non-obesity MASLD group. The recognition of MASLD and its body weight phenotypes will be beneficial in the prognostication following AMI.
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Jaycie Koh
Nanyang Technological University
Ayman Mohamed
Zagazig University
Gwyneth Kong
National University Hospital
Diabetes Obesity and Metabolism
King's College London
National University of Singapore
Nanyang Technological University
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Koh et al. (Mon,) studied this question.
synapsesocial.com/papers/6a07f8520511025d3a378ae3 — DOI: https://doi.org/10.1111/dom.16062
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