Wei Li1 , Jing Huang1 , Hua Li1 , Tingchun Gou1 , Ling Tang1 , Xuesu Dong1 and Chunmei Luo2*

*Correspondence: Chunmei Luo 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。

1  Department of Anesthesiology, Xinqiao Hospital, Army Medical University, Chongqing, P.R. China

2 Department of Orthopedics, Xinqiao Hospital, Army Medical University,83 Xinqiao Main Street, Shapingba District, Chongqing 400037, P.R. China

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Abstract

Objective To construct a model for predicting the risk of IAPI (Intraoperative acquired pressure injury) in the facial area of patients undergoing prone position surgery and to validate the predictive effectiveness of this model.

Methods We analyzed data from 970 patients who underwent prone position surgery at a tertiary general hospital in Chongqing, China, from January 2022 to October 2022. Using univariate analysis and logistic regression analysis, we identified risk factors for IAPI in the maxillofacial region of patients undergoing prone position surgery and constructed a nomogram prediction model using R software. On the basis of the selected predictive factors, a risk prediction model was constructed and evaluated using the concordance index (C-index) and the area under the curve (AUC). External validation was conducted to verify the model’s performance.

Results The incidence of IAPI in prone surgery patients was 17.8%. Multivariate logistic regression analysis revealed  that BMI, history of diabetes, surgical duration, muscle relaxant dosage, history of allergies, and preoperative Braden score were the most important factors for the occurrence of intraoperative pressure injuries in the facial region of patients who underwent prone position surgery (P<0.05). The area under the ROC curve of the prediction model is 0.863, the maximum Youden index is 0.681, the optimal cutoff value is 0.214, the sensitivity is 0.815, the specificity is 0.866, and the accuracy in actual application is 91.1%.

Conclusions The IAPI risk prediction model for maxillofacial surgery patients in the prone position constructed in this study demonstrated good predictive performance, providing a basis for clinical medical staff to quickly identify high risk patients and implement precise intervention plans before surgery.

Keywords Pressure ulcer, Prone position, Maxillofacial, Nomogram, Prediction model