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Sanshun Zhou

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Open access Aug 2026

Predictive Value of the Systemic Immune-Inflammation Index Combined With the Prognostic Nutritional Index for Flap-Related Complications Following Flap Repair in Patients With Stage Ⅲ and Ⅳ Pressure Injuries.

AIM To investigate the combined predictive value of systemic immune-inflammation index (SII) and prognostic nutritional index (PNI) for postoperative flap-related complications in patients with stage Ⅲ and Ⅳ pressure injuries undergoing flap repair. METHODS A single-center retrospective cohort study was conducted. A total of 242 patients with stage Ⅲ and Ⅳ pressure injuries who underwent flap repair between January 2020 and December 2024 were enrolled. Based on postoperative flap-related complications, patients were divided into a non-complication group (n = 181) and a complication group (n = 61). Preoperative clinical data and laboratory parameters were collected, and SII and PNI were calculated. Independent risk factors were identified using univariate and multivariate logistic regression analyses, and a nomogram prediction model was subsequently developed. Receiver operating characteristic (ROC) and calibration curves were used to evaluate the predictive performance of the model. RESULTS Multivariate analysis demonstrated that PNI (odds ratio (OR) = 0.851, 95% CI: 0.793-0.913), SII (OR = 1.307, 95% CI: 1.143-1.494), and intraoperative blood loss (OR = 2.150, 95% CI: 1.141-4.052) were independent predictors of postoperative flap-related complications. The area under the curve (AUC) of the prediction model based on these three variables was 0.88 (95% CI: 0.83-0.93). The calibration curve demonstrated good agreement between predicted and observed outcomes (Hosmer-Lemeshow test, p = 0.335). CONCLUSIONS Elevated preoperative SII, reduced preoperative PNI, and increased intraoperative blood loss are independent risk factors for flap-related complications following flap repair in patients with stage Ⅲ and Ⅳ pressure injuries. The prediction model based on these three factors demonstrates good discrimination and calibration, which may facilitate perioperative risk assessment and provide a basis for individualized clinical interventions.

Sanshun Zhou, Linjun Wu, Dongqian Xie · 0 citations

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