ArticleEuropean journal of medical research2025
Group-based trajectory modeling of anion gap and mortality in patients with sepsis: a retrospective analysis of the MIMIC-IV database.
Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Association between post-void residual urine volume trajectories and incident urinary tract infection in patients receiving maintenance hemodialysis.BMC nephrology · 2026Article
- Association between anion gap trajectories and mortality in patients with acute cholangitis: a cohort study.Scientific reports · 2026Article
- Group-based trajectory modeling of blood pressure reactivity and mortality in septic patients: a retrospective study of the MIMIC-IV database.BMC infectious diseases · 2026Article
- Effect modification by chronic obstructive pulmonary disease, anion gap, and serum creatinine on the association between invasive mechanical ventilation and 28-day mortality in intensive care unit sepsis patients: a retrospective cohort study.Frontiers in medicine · 2026Article
- Machine Learning-Based Nomogram with Boruta and LASSO for 28-Day Mortality Prediction in Critical COPD Patients: Role of the Albumin-Corrected Anion Gap.International journal of chronic obstructive pulmonary disease · 2026Article
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9 authors.
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Abstract
backgroundThe purpose of this study was to identify distinct trajectories of the anion gap (AG) of patients with sepsis within the first 48 h following intensive care unit (ICU) admission and to explore the relationship between these trajectories and all-cause mortality.
methodsThis study was carried out involving patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Group-based trajectory modeling (GBTM) was utilized to identify the distinct trajectory groups for the AG values. The primary outcome was 30-day mortality, and the secondary outcomes were 90-day and 1-year mortality. Both univariable and multivariable Cox proportional hazards regression models were performed to explore the relationship between different AG longitudinal trajectories and mortality. Stratified analyses were performed to investigate the stability of the relationship between AG trajectories and the primary outcome.
resultsA total of 6960 patients with sepsis were included for trajectory grouping. Four distinct AG trajectories based on the model fitting standard were identified: group 1 (11.19%), group 2 (52.87%), group 3 (29.86%), and group 4 (6.08%). Using trajectory group 1 as the reference, after adjusting for all potential confounders, group 2, group 3, and group 4 still had 1.32 (95% confidence interval [CI] 1.07-1.63), 1.67 (95% CI 1.33-2.09), and 1.87 (95% CI 1.40-2.51) times the risk of 30-day mortality, respectively. Similar results were also found for 90-day mortality and 1-year mortality. The associations were directionally similar across all subgroups.
conclusionsTrajectory groups with higher AG levels were associated with an increased risk for all-cause mortality. Identifying distinct AG trajectories may help identify patient subgroups with varying risks of mortality, providing valuable implications for both research and clinical practice.
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