高乳酸血症
医学
星团(航天器)
败血症
逻辑回归
危险系数
内科学
置信区间
计算机科学
程序设计语言
作者
Zhihui Liang,Min Zhao,Kaiting Liu,Weican Liang,Shaofang Luo,Jianbin Guan,Zongmian Zhang
出处
期刊:Shock
[Lippincott Williams & Wilkins]
日期:2025-07-28
标识
DOI:10.1097/shk.0000000000002653
摘要
Abstract Background The evolution of lactate levels reflects the complex pathophysiological processes in sepsis. Whether distinct subclusters of sepsis exhibit different lactate trajectories remains unclear. This study aimed to identify novel clusters of sepsis based on lactate trajectories and investigate the association between lactate trajectory and mortality risk, and to develop a predictive model for unfavorable lactate trajectories. Methods Early survivors diagnosed with sepsis were included. A group-based trajectory model (GBTM) was constructed to identify distinct lactate trajectories. Doubly robust estimation models were utilized to assess the association between each cluster and mortality risk. A cross-lagged panel model (CLPM) was applied to examine the temporal causal relationship between lactate levels and sequential organ failure assessment (SOFA) score. LASSO-logistic regression was used to develop a predictive model for unfavorable lactate trajectories. Results A total of 4870 patients from two critical care medicine databases were included. Four lactate trajectory clusters were identified: 1. hyperlactatemia, gradual resolution (cluster 1;14.0%), 2. consistent near-normal lactate level (cluster 2; 81.5%), 3. extreme hyperlactatemia at admission but with prompt clearance (cluster 3; 2.0%), and 4. consistent hyperlactatemia (cluster 4; 2.5%). Comparisons were conducted using cluster 1 as the reference. Cluster 2 showed reduced 28-day mortality risk (HR 0.76; 95%CI 0.65 to 0.89), while no difference was observed in adjusted mortality hazard risk. Clusters 3 and 4 had higher mortality risks (HR 1.94; 95%CI 1.40 to 2.67 and HR 3.87; 95%CI 2.98 to 5.03 respectively) compared to cluster 1. The CLPM analysis showed a bidirectional causal relationship between lactate levels and organ dysfunction (Lactate→SOFA,β = 0.310,P < 0.001 vs. SOFA→Lactate,β = 0.037,P < 0.001). A nomogram with five variables was developed to identify unfavorable lactate trajectories. Conclusion Lactate trajectories are significantly associated with mortality risk in early-survival patients with sepsis, which provides an valuable framework for risk stratification in sepsis.
科研通智能强力驱动
Strongly Powered by AbleSci AI