Association between endothelial activation and stress index and all-cause mortality risk in sepsis patients: a retrospective cohort analysis utilizing the MIMIC-IV database
Bibliographic record
Abstract
The Endothelial Activation and Stress Index (EASIX) has recently gained attention as an emerging indicator of endothelial injury, which significantly contributes to the progression of sepsis. Nevertheless, the association between EASIX levels and mortality outcomes in sepsis has yet to be fully clarified. This study explored the clinical significance of EASIX in septic patients admitted to the intensive care unit (ICU). Data of sepsis patients were acquired from the Medical Information Mart for Intensive Care (MIMIC) database and analyzed. Participants were categorized into three groups according to their log2–EASIX values. The interplay between the mortality and log2–EASIX values in individuals with sepsis was examined via Cox regression analysis. To explore possible nonlinear relationships between log2–EASIX values and sepsis-related mortality, we applied a restricted cubic spline (RCS) model. Additionally, Kaplan–Meier (KM) and subgroup analyses were conducted to evaluate the robustness of the findings. A total of 8829 individuals diagnosed with sepsis were included in this study. Elevated log2–EASIX levels were consistently associated with a higher likelihood of mortality throughout all assessed time frames. Patients with the highest log2–EASIX scores exhibited a markedly elevated risk of death, with hazard ratios (HRs) of 1.56 at 30 days, 1.44 at 60 days, 1.38 at 90 days, 1.31 at 180 days, and 1.29 at 365 days. While the association was strongest in the early phase, elevated mortality risk persisted throughout the follow-up period. Moreover, an alternative statistical approach, specifically the use of RCS, exhibited a steady linear link between log2–EASIX values and mortality risk across all considered time points. This study demonstrated that EASIX is independently and positively associated with mortality in patients with sepsis. Elevated EASIX levels were correlated with increased disease severity and poorer clinical outcomes, suggesting its potential utility as a risk stratification indicator in critical care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".