Role of regional tissue oxygen saturation (rSO₂) monitoring in lower limb ischemia during VA-ECMO: a retrospective case study

Abstract Background and objectives VA-ECMO can provide circulatory support for critically ill patients with cardiogenic failure for periods ranging from several days to months; however, it may result in lower limb ischemia. This study aims to analyze and investigate the risk factors contributing to lower limb ischemia in VA-ECMO patients. Methods This study included 40 consecutive patients who received veno-arterial extracorporeal membrane oxygenation (VA-ECMO) support therapy and were admitted to the Intensive Care Unit (ICU) of the People's Hospital of Guangxi Zhuang Autonomous Region from May 2024 to May 2025. By analyzing and comparing differences in baseline characteristics, multivariate logistic regression analysis was applied to identify independent risk factors for lower extremity ischemia in patients treated with VA-ECMO. Results Among 40 VA-ECMO patients, 12 (30%) developed lower limb ischemia. Compared to the non-ischemia group, the ischemia group showed significantly lower values in regional oxygen saturation (rSO₂), bilateral lower limb rSO₂ difference, femoral catheter-to-artery diameter ratio (d/D), and antithrombin III (AT-III) levels (p Logistic regression analysis demonstrated that rSO₂ more accurately reflects the status of lower limb ischemia, with rSO₂, bilateral rSO₂ difference, d/D ratio, and AT-III all showing statistical significance. Multifactorial binary logistic regression analysis identified bilateral rSO₂ difference as an independent predictor of lower limb ischemia (OR = 1.692, p ROC curve analysis demonstrated that rSO₂ had a high predictive value for lower limb ischemia risk, with the highest predictive performance (AUC = 0.982) achieved through combined biomarker assessment. Conclusions rSO₂ monitoring enables early prediction of lower limb ischemia in VA-ECMO patients, demonstrating significant clinical value. When combined with complementary biomarkers, it further enhances predictive accuracy, offering high utility in clinical practice.