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Predictive Value of the Systemic Immune-Inflammation Index Combined With the Prognostic Nutritional Index for
Sanshun Zhou1, Linjun Wu1, Dongqiang Xie1
1Department of Wound Repair, Hangzhou First People's Hospital Chengbei Campus, Hangzhou Geriatric Hospital, 310022 Hangzhou, Zhejiang, China.
Insights
Elevated systemic immune-inflammation index (SII) and reduced prognostic nutritional index (PNI) predict flap complications after pressure injury repair. This finding aids perioperative risk assessment for better patient outcomes.
Area of Science:
- Plastic Surgery
- Surgical Oncology
- Wound Healing Research
Background:
- Stage III and IV pressure injuries present significant challenges in flap repair.
- Postoperative flap-related complications can lead to prolonged recovery and increased morbidity.
Purpose of the Study:
- To evaluate the combined predictive value of the systemic immune-inflammation index (SII) and prognostic nutritional index (PNI) for postoperative flap complications.
- To develop a predictive model for flap complications in patients undergoing flap repair for severe pressure injuries.
Main Methods:
- A retrospective cohort study of 242 patients with stage III-IV pressure injuries undergoing flap repair.
- Calculation of preoperative SII and PNI, with logistic regression analysis to identify independent predictors.
- Development and validation of a nomogram prediction model using ROC and calibration curves.
Main Results:
- Elevated SII (OR=1.307), reduced PNI (OR=0.851), and increased intraoperative blood loss (OR=2.150) were independent predictors of flap complications.
- The prediction model achieved an AUC of 0.88 (95% CI: 0.83-0.93), indicating good discriminative ability.
- The model demonstrated good calibration, with no significant difference between predicted and observed outcomes (p=0.335).
Conclusions:
- Preoperative SII, PNI, and intraoperative blood loss are key risk factors for flap complications in severe pressure injury repair.
- The developed prediction model offers robust discrimination and calibration for perioperative risk assessment.
- This model can guide individualized clinical interventions to mitigate flap-related complications.
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.
