DOI: 10.62713/aic.4634 ISSN: 0003-469X

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

Sanshun Zhou, Linjun Wu, Dongqiang Xie

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.

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