RDW trajectories during sepsis hospitalization predict 30- and 90-day mortality in retrospective study
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Key Takeaway
Consider RDW trajectory patterns as an associative risk signal in sepsis, pending prospective validation.
This retrospective cohort study analyzed data from 3,813 sepsis patients in the MIMIC-IV database (derivation cohort) and 467 patients from a separate hospital (external validation cohort). The research examined the association between red blood cell distribution width (RDW) trajectories over the first 10 days of hospitalization and mortality outcomes, comparing three identified trajectory patterns.
The main results showed that patients with Trajectory 3 had significantly increased mortality compared to those with Trajectory 1 (Slow-Decrease). For 30-day mortality, the hazard ratio was 1.47 (95% CI 1.17–1.84). For 90-day mortality, the hazard ratio was 1.54 (95% CI 1.25–1.88). Trajectory 2 was associated with the most favorable survival rates, though specific numbers were not reported. Safety and tolerability data were not reported.
Key limitations include the observational design, which precludes causal inference, and potential limited generalizability as the study population may represent patients with more severe illness. The frequency of RDW testing was also noted as a limitation. External validation confirmed the model's robustness, but the findings require prospective confirmation.
For practice, this study suggests RDW trajectory patterns could serve as a dynamic risk stratification tool in sepsis management. However, clinicians should interpret these findings cautiously as an associative signal rather than a proven causal relationship, awaiting further evidence before integrating trajectory analysis into routine clinical decision-making.
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View Original Abstract ↓
BackgroundThe 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.MethodsWe conducted a retrospective cohort study using data from the MIMIC-IV database (n = 3,813) as the derivation cohort and from the First Affiliated Hospital of Kunming Medical University (n = 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.ResultsA 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.ConclusionThis 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.
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