11/24/2023 0 Comments Plexiform layersOf 249 metabolic metrics, 37 were independently associated with GCIPLT, including 8 positive and 29 negative associations, and most were associated with the rates of future mortality and common diseases. Results Among 93 838 community-based participants (51 182 women), the mean (SD) age was 56.7 (8.1) years and mean (SD) follow-up was 12.3 (0.8) years. Main Outcomes and Measures Systematic analysis of circulating plasma metabolites to identify GCIPLT metabolic profiles prospective associations of these profiles with mortality and morbidity of 6 common diseases with their incremental discriminative value and clinical utility. Additional participants from the Guangzhou Diabetes Eye Study (GDES) underwent optical coherence tomography scanning and metabolomic profiling and were included for validation. Objective To investigate the independent associations of retinal ganglion cell–inner plexiform layer thickness (GCIPLT) metabolic profiles with rates of mortality and morbidity of common diseases.ĭesign, Setting, and Participants This cohort study evaluated UK Biobank participants enrolled between 20, and prospectively followed them up for multidisease diagnosis and mortality. Importance The neural retina is considered a unique window to systemic health, but its biological link with systemic health remains unknown. Shared Decision Making and Communication.Scientific Discovery and the Future of Medicine.Health Care Economics, Insurance, Payment.Clinical Implications of Basic Neuroscience.Challenges in Clinical Electrocardiography.Sensitivity Analysis of Excluding All Missing Values List Summarizing Metabolic Profiles Identified in the GDES Cohort Using LC/MS ProfilingĮTable 10. NRIs Improvements of Incorporating GCIPLT Metabolic Profiles for Mortality and Morbidity of Common DiseasesĮTable 9. Discriminative Power of Clinical Indicators and GCIPLT Metabolic Profiles for Predicting Mortality and Common DiseasesĮTable 8. Number of Incident Health Outcomes in Total, Discovery Set, and Validation SetĮTable 7. Significant Metabolites Associated With GCIPLTĮTable 6. Baseline Characteristics of the Study Population from the GDES CohortĮTable 5. Baseline Characteristics of the Study Population from the UKB CohortĮTable 4. Metabolic Markers Used in Models Discriminating Common Diseases and MortalityĮTable 3. List Summarizing All Metabolic Markers Quantifying Using 1H-NMR ProfilingĮTable 2. Net Benefit Curves of Clinical Utility for Common Diseases and MortalityĮTable 1. Calibration Plots Illustrating Predicted and Observed Probabilities for Common Diseases and MortalityĮFigure 9. Receiver Operating Characteristic Curves of Clinical Indicators-based Models, GCIPLT Metabolic State Models, and Combined Models for Predicting Common Diseases and MortalityĮFigure 8. Predictive Power of GCIPLT Metabolic Profiles and Clinical Indicators for Common Diseases and MortalityĮFigure 7. Cumulative Event Rates Over the Observation Time for Common Diseases and MortalityĮFigure 6. Associations of GCIPLT Metabolic Profiles and Risk of Morbidity of Common Diseases and MortalityĮFigure 5. Heatmaps Demonstrating the Overall Correlations of GCIPLT and MetabolitesĮFigure 4. Analytic Framework of the StudyĮFigure 3.
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