Abstract
OBJECTIVE: To investigate the association between renal mean perfusion pressure (MPP) and prognosis in sepsis-associated acute kidney injury (SA-AKI). METHODS: Data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Group-based trajectory modeling (GBTM) was applied to identify dynamic MPP patterns, while restricted cubic spline (RCS) curves were utilized to confirm the non-linear relationship between MPP and mortality. Cox regression analysis assessed the risk of mortality across different MPP levels, adjusting for potential confounders. Subgroup analyses and sensitivity analyses were conducted to ensure the robustness of the findings. RESULTS: A total of 2318 patients with SA-AKI were stratified into five MPP trajectories by GBTM. Patients in Traj-1 and Traj-2, characterized by consistently low MPP (<60 mmHg), demonstrated markedly higher 90-d mortality (62.86% and 26.98%). RCS curves revealed a non-linear inverse relationship between MPP and 90-d mortality, identifying 60 mmHg as the optimal threshold. Patients with MPP ≤ 60 mmHg exhibited significantly elevated 90-d mortality compared to those with MPP > 60 mmHg (29.81% vs. 20.88%). Cox regression analysis established Traj-1 and Traj-2 as independent risk factors for increased mortality relative to Traj-3 (60-70 mmHg), with hazard ratios (HRs) of 4.67 (95%-CI 3.28-6.67) and 1.45 (95%-CI 1.20-1.76). MPP > 60 mmHg was significantly associated with reduced 90-d mortality (HR 0.65, 95%-CI 0.55-0.77). Subgroup and PSM analyses supported these findings. CONCLUSIONS: Dynamic MPP trajectory serves as a valuable prognostic biomarker for SA-AKI. Early monitoring of MPP trends offers critical insights into renal perfusion management, potentially improving outcomes in SA-AKI.