Metabolic Biomarkers and Endotypes as Predictors of Sepsis Outcomes: A Prospective Population-Based Cohort Analysis from the UK Biobank

作者：Hao Bai, Yihui Li, Yue Xue, Shaohua Zhao, Tingyu Meng, Ming Lu, Hao Wang · 发表于：Research Square · 年份：2024 · DOI：10.21203/rs.3.rs-4365014/v1 · 研究领域：Sepsis Diagnosis and Treatment、Hyperglycemia and glycemic control in critically ill and hospitalized patients、Metabolomics and Mass Spectrometry Studies

Abstract Background Understanding the impact of population metabolic landscapes on susceptibility and outcomes of sepsis is crucial for guiding clinical consultations. This study explores the relationship between plasma metabolites and the incidence and mortality of sepsis among affected populations. Methods The analysis utilized data from the UK Biobank community study, which involved Nuclear Magnetic Resonance (NMR) spectroscopy of 118,461 baseline plasma samples generated by Nightingale Health, up to December 31, 2013. Risk factors were identified through multivariate logistic regression analysis. Finally, principal component analysis was used to determine the major influencing factors. The data analysis period was from October 1, 2023, to December 1, 2023. Cox regression analysis was conducted to produce adjusted hazard ratios (HR) for the relationships between individual metabolic biomarkers and 11 principal components of metabolic biomarkers (which together explained 90% of the total variance in individual biomarkers) and their association with the incidence and mortality of sepsis. Results A total of 106,533 participants were included in the primary analysis (average age 60.67 years and 96% Caucasian). Total 3,486 cases of sepsis as defined by the study were identified, and among these, 635 instances of sepsis-related mortality occurred. The results showed that lipid and related lipoprotein (HR from 0.89 to 0.95), albumin (HR, 0.87 ,95% (confidence interval) CI, 0.84–...