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Hemodynamic Predictors for Sepsis-Induced Acute Kidney Injury: A Preliminary Study
Oana Antal1,2, Elena Ștefănescu1,2, Monica Mleșnițe1,2
1Department of Anaesthesia and Intensive Care, "Iuliu Hațieganu" University of Medicine and Pharmacy, No 3-5 Clinicilor Street, Cluj-Napoca, 400005 Cluj, Romania.
Abstract:
The aim of our study was to assess the association between the macrohemodynamic profile and sepsis induced acute kidney injury (AKI). We also investigated which minimally invasive hemodynamic parameters may help identify patients at risk for sepsis-AKI. We included 71 patients with sepsis and septic shock. We performed the initial fluid resuscitation using local protocols and continued to give fluids guided by the minimally invasive hemodynamic parameters. We assessed the hemodynamic status by transpulmonary thermodilution technique. Sequential organ failure assessment (SOFA score) (AUC 0.74, 95% CI 0.61-0.83, p < 0.01) and cardiovascular SOFA (AUC 0.73, 95% CI 0.61-0.83, p < 0.01) were found to be predictors for sepsis-induced AKI, with cut-off values of 9 and 3 points respectively. Persistent low stroke volume index (SVI) ≤ 32 mL/m2/beat (AUC 0.67, 95% CI 0.54-0.78, p < 0.05) and global end-diastolic index (GEDI) < 583 mL/m2 (AUC 0.67, 95% CI 0.54-0.78, p < 0.05) after the initial fluid resuscitation are predictive for oliguria/anuria at 24 h after study inclusion. The combination of higher vasopressor dependency index (VDI, calculated as the (dobutamine dose × 1 + dopamine dose × 1 + norepinephrine dose × 100 + vasopressin × 100 + epinephrine × 100)/MAP) and norepinephrine, lower systemic vascular resistance index (SVRI), and mean arterial blood pressure (MAP) levels, in the setting of normal preload parameters, showed a more severe vasoplegia. Severe vasoplegia in the first 24 h of sepsis is associated with a higher risk of sepsis induced AKI. The SOFA and cardiovascular SOFA scores may identify patients at risk for sepsis AKI. Persistent low SVI and GEDI values after the initial fluid resuscitation may predict renal outcome.
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