Three distinct trajectories of red blood cell distribution width and their significant associations with mortality in sepsis patients: a group-based trajectory modeling study with validation

Background: The red cell distribution width (RDW) is a recognized prognostic marker in sepsis, yet its dynamic changes over time and their relationship with outcomes remain unexplored. This study aimed to identify distinct RDW trajectories during the early phase of sepsis and evaluate their association with mortality. Methods: = 467) for external single-center validation. Sepsis patients with at least seven RDW measurements within the first 10 days of hospitalization were included. Group-based trajectory modeling (GBTM) was employed to identify RDW trajectories. Results: A three-trajectory model was selected based on model fit indices and clinical interpretability: Trajectory 1 (Slow-Decrease, 32.97%), Trajectory 2 (Slow-Increase, 43.30%), and Trajectory 3 (Fluctuating-Rapid Decrease, 23.73%). In our study, Cox models adjusted for confounders revealed that, compared to Trajectory 1, Trajectory 3 was independently associated with significantly increased 30-day (HR 1.47, 95% CI 1.17-1.84) and 90-day mortality (HR 1.54, 95% CI 1.25-1.88). Conversely, Trajectory 2 was associated with the most favorable survival rates. Kaplan-Meier analysis consistently showed the highest mortality in the Trajectory 3 group. External validation confirmed the model's robustness and the consistent prognostic value of the identified trajectories. Conclusion: This study is the first to apply trajectory modeling to identify three dynamic RDW trajectories with significant prognostic stratification in sepsis patients. Among them, the "fluctuating-rapid decline" trajectory is an independent risk factor for both 30-day and 90-day mortality. However, due to the limitation of RDW testing frequency, the study may represent a group with more severe illness, which may limit the generalizability of the conclusions. This discovery elevates the conventional indicator RDW into a dynamic and practical bedside risk stratification tool, which may assist clinicians in early identification of high-risk patients.