Data Sheet 1_Association between osmolality trajectories and mortality in patients with sepsis: a group-based trajectory model in large ICU open access databases.docx

ObjectiveThe regulation of osmolality levels is controlled by the endocrine system, reflecting the body’s water and electrolyte balance. However, the relationship between dynamic osmolality trajectories and the prognosis of septic patients has not yet been reported. This study aims to investigate the predictive value of dynamic osmolality trajectories on mortality among patients with sepsis.
MethodsA retrospective analysis was performed using the MIMIC IV and eICU-CRD databases. A total of 19,502 patients were included, 10,263 from MIMIC IV and 9,239 from eICU-CRD. Group-based trajectory modeling (GBTM) analysis was performed to identify distinct osmolality trajectories. The association between these trajectories and in-hospital mortality was assessed by logistic regression analysis and further adjusted for potential confounders. Subgroup analysis was used to identify potential interactive factors and to assess the robustness of the present findings.
ResultsFive distinct osmolality trajectories were identified. Patients in the persistent hyperosmolality trajectory (Trajectory-5) had significantly higher in-hospital mortality compared to other trajectories, with an increased risk of in-hospital mortality of 233% (OR 3.33, 95% CI 2.71–4.09) and 150% (OR 2.50, 95% CI 1.97–3.17) in MIMIC IV and eICU-CRD respectively, with Trajectory-2 as reference. A dynamic increase in osmolality (Trajectory-4) was also associated with a 68% (OR 1.68, 95% CI 1.39–2.03) and a 68% (OR 1.68, 95% CI 1.44–1.97) increase in the risk of death, compared with Trajectory-2. Conversely, maintaining osmolality in the range of 290–300 mOsm/L (Trajectory-1 and Trajectory-2) was associated with a lower risk of death. Our results remained stable in the IPWRA and subgroup analyses.
ConclusionOur findings suggest that dynamic changes in plasma osmolality are significantly associated with in-hospital mortality in septic patients. Osmolality trajectory model provides a potentially effective, easily accessible and cost-effective biomarker for the prognostic assessment and clinical management of sepsis.