Nomogram Model for Predicting Pressure Injury in COPD Patients Using SII: A Chinese Clinical Study

Yuli Cai ¹ Huimin Chen ¹ Zhaojun Chen ¹ Qinghua Chen ¹ Yihuan Su ¹ Feiju Chen ¹ Jingjing Pan ¹ Yitian Yang ¹ Zhongxing Hu ² Wenxi Li ¹ Huizhao Liao ³ Tingting Sun ³ Junfen Cheng ¹ Wenliang Chen ¹ Baozhi Zhang ¹ Riken Chen ^1*

• ¹ Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
• ² Zhengzhou University, Zhengzhou, Henan Province, China
• ³ State Key Laboratory of Respiratory Diseases, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China

Objective: This study aims to investigate the association between the Systemic Immune-Inflammation Index (SII) and the development of pressure injuries (PI) in patients with chronic obstructive pulmonary disease (COPD). Additionally, a nomogram model based on the SII will be constructed to predict the probability of pressure injury (PI) occurrence in patients with COPD.A retrospective analysis was performed on the clinical data of 844 patients with COPD who were admitted to the Affiliated Hospital of Guangdong Medical University between June 2018 and December 2019. Logistic regression analysis was employed to identify risk factors associated with the development of PI, and the Wald chi-square test was used to select variables for constructing a predictivenomogram. The performance of the nomogram was assessed, followed by internal validation. Additionally, clinical data from 452 patients with COPD admitted to the Second Affiliated Hospital of Guangdong Medical University between January 2024 and December 2024 were prospectively collected for external validation.Results: A total of 844 patients with COPD were included in this study, with 590 cases in the training group and 254 cases in the internal validation group. The predictors included in the nomogram model were age, respiratory rate (Breathe [R]), duration of COPD history, Serum albumin(ALB), SII, paralysis, edema, and activities of daily living (ADL). The nomogram demonstrated strong predictive performance and calibration. The area under the curve and 95% confidence intervals were 0.77 (0.72-0.82) for the training group, 0.77 (0.70-0.85) for the internal validation group, and 0.73 (0.66-0.81) for the external validation group.This study identified the SII, age, respiratory rate, duration of COPD history, ALB, paralysis, and ADL as independent risk factors for the development of PI in patients with COPD. A nomogram model was successfully developed based on SII and validated through both internal and external testing. The findings suggest that SII is a reliable predictor of PI development in patients with COPD, and the model demonstrates strong predictive performance.