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Identifying biomarker-driven subphenotypes of cardiogenic shock: analysis of prospective cohorts and randomized controlled trials.
EClinicalMedicine
January 2025
University of Paris Cité, Inserm UMR-S 942, Cardiovascular Markers in Stress Conditions (MASCOT), Paris, France.
Background: Cardiogenic shock (CS) is a heterogeneous clinical syndrome, making it challenging to predict patient trajectory and response to treatment. This study aims to identify biological/molecular CS subphenotypes, evaluate their association with outcome, and explore their impact on heterogeneity of treatment effect (ShockCO-OP, NCT06376318).
Methods: We used unsupervised clustering to integrate plasma biomarker data from two prospective cohorts of CS patients: CardShock (N = 205 [2010-2012, NCT01374867]) and the French and European Outcome reGistry in Intensive Care Units (FROG-ICU) (N = 228 [2011-2013, NCT01367093]) to determine the optimal number of classes.
Machine learning derivation of two cardiac arrest subphenotypes with distinct responses to treatment.
J Transl Med
January 2025
Fourth Clinical Medical College of Zhejiang Chinese Medical University, Zhejiang, 310006, Hangzhou, China.
Introduction: Cardiac arrest (CA), characterized by its heterogeneity, poses challenges in patient management. This study aimed to identify clinical subphenotypes in CA patients to aid in patient classification, prognosis assessment, and treatment decision-making.
Methods: For this study, comprehensive data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) 2.
Aiming for precision: personalized medicine through sepsis subtyping.
Burns Trauma
January 2025
Amsterdam University Medical Center, University of Amsterdam, Center of Experimental and Molecular Medicine & Division of Infectious Diseases, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands.
According to the latest definition, sepsis is characterized by life-threatening organ dysfunction caused by a dysregulated host response to an infection. However, this definition fails to grasp the heterogeneous nature and the underlying dynamic pathophysiology of the syndrome. In response to this heterogeneity, efforts have been made to stratify sepsis patients into subtypes, either based on their clinical presentation or pathophysiological characteristics.
View Article and Find Full Text PDFSubphenotypes of body composition and their association with cardiometabolic risk - Magnetic resonance imaging in a population-based sample.
Metabolism
December 2024
Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany. Electronic address:
Background: For characterizing health states, fat distribution is more informative than overall body size. We used population-based whole-body magnetic resonance imaging (MRI) to identify distinct body composition subphenotypes and characterize associations with cardiovascular disease (CVD) risk.
Methods: Bone marrow, visceral, subcutaneous, cardiac, renal, hepatic, skeletal muscle and pancreatic adipose tissue were measured by MRI in n = 299 individuals from the population-based KORA cohort.
Rapid identification and phenotyping of nonalcoholic fatty liver disease patients using a machine-based approach in diverse healthcare systems.
Clin Transl Sci
January 2025
Division of Digestive and Liver Diseases, Department of Medicine, Center for Liver Disease and Transplantation, Columbia University Irving Medical Center, New York, New York, USA.
Nonalcoholic fatty liver disease (NAFLD) is the most common global cause of chronic liver disease and remains under-recognized within healthcare systems. Therapeutic interventions are rapidly advancing for its inflammatory phenotype, nonalcoholic steatohepatitis (NASH) at all stages of disease. Diagnosis codes alone fail to recognize and stratify at-risk patients accurately.
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