Systemic immune inflammatory index (SII) and systemic inflammatory response index (SIRI) as predictors of postoperative delirium in patients undergoing off-pump coronary artery bypass grafting (OPCABG) with cerebral infarction.

Zhao, Bing-sha; Zhai, Wen-qian; Ren, Min; Zhang, Zhao; Han, Jian-ge

Objective: Postoperative delirium (POD) is a common complication following off-pump coronary artery bypass grafting (OPCABG) and is associated with significant morbidity. This study aims to evaluate the correlation of systemic immune inflammatory index (SII) and systemic inflammatory response index (SIRI) with postoperative delirium (POD) in patients with cerebral infarction undergoing OPCABG. Methods: The perioperative cohort study included 321 patients who underwent OPCABG. Patients were divided into two groups based on the occurrence of POD: the delirium group (n = 113) and the non-delirium group (n = 208). Baseline characteristics, including gender, left ventricular ejection fraction (LVEF), surgery duration, hypertension, age, and smoking history were analyzed. SII and SIRI values were calculated preoperatively, and their association with POD was assessed using univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curves were used to evaluate the predictive accuracy of SII and SIRI. Results: Statistical differences between SII and SIRI in the two groups (P < 0.05) were observed. Multivariate analysis confirmed that SII and SIRI, age and preoperative smoking history were predictors of POD. ROC curve analysis demonstrated that SII and SIRI had considerable predictive power, with AUC values of 0.73 (0.67–0.79) for SII and 0.75 (0.69–0.81) for SIRI. Conclusion: SII and SIRI were found to be associated with an increased risk of POD in patients undergoing OPCABG, but further research is needed to confirm these findings and determine their independence as risk factors.

CORONARY artery bypass; CEREBRAL infarction; RECEIVER operating characteristic curves; VENTRICULAR ejection fraction; LOGISTIC regression analysis

BMC Surgery, 2024, Vol 24, Issue 1, p1

1471-2482

Academic Journal

10.1186/s12893-024-02598-7