Predicting Wound Complications Following Total Knee Arthroplasty: Preoperative Inflammatory Indices and a Novel Risk...

Background/Objectives: This study investigated the value of several hemogram-derived biomarkers, including SIRI, SII, PIIV, NLR, MLR, and PLR, in predicting wound complications after total knee arthroplasty (TKA). Methods: This study involved 226 patients who underwent TKA between 2018 and 2024. Preoperative hematological parameters and their derived indices (NLR, MLR, PLR, PIIV, SII, and SIRI) were analyzed. To identify the parameters that predict the risk of complications, correlation analysis, ROC-curve analysis, and logistic regression analysis were performed. Additionally, a novel risk scale, entitled "Preoperative Inflammatory Index at Total Knee Arthroplasty (TKA-PII)", was developed using factor analysis and a reliability test. Results: Postoperative wound complications were observed in 30 patients. NLR, MLR, PIIV, SII, and SIRI values were significantly higher in those who developed complications. Correlation analysis indicated a positive relationship between these inflammatory indices and the risk of developing complications. ROC-Curve analysis revealed that SIRI had the highest discriminative performance (area under curve (AUC) = 0.720), followed closely by PIIV (AUC = 0.716) and SII (AUC = 0.704) in predicting the complication risk. Logistic regression analysis identified that SIRI was the best predictor of postoperative wound complications (Odds Ratio = 2.277, p = 0.004). Additionally, the TKA-PII scale demonstrated acceptable validity and reliability (Bartlett's test of sphericity = 0.609, Cronbach's alpha = 0.647). Conclusions: This study's findings suggest that preoperative hemogram-derived inflammatory indices, particularly SIRI, could be valuable markers for predicting the risk of wound complications after TKA. Furthermore, the newly developed TKA-PII scale could be used as an easy-to-use and cost-effective tool for preoperative risk assessment in clinical practice.