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Using a Decision Tree Approach to Analyze Key Factors Influencing Intraoperative-Acquired Pressure Injury
Guirong Shi1, Liping Jiang, Ping Liu
1At Xinhua Hospital, affiliated with Shanghai Jiaotong University School of Medicine, Shanghai, China, Guirong Shi, MSN, RN, is Specialty Nurse; Liping Jiang, PhD, RN, is Director of the Nursing Department; and Ping Liu, MSN, RN, is Associate Director of the Nursing Department. Xin Xu, RN, is Graduate Student, School of Nursing, Wenzhou Medical University, Zhejiang. Also at Xinhua Hospital, Qunfang Wu, BS, RN, is Nursing Supervisor of the Spine Center; and Peipei Zhang, BS, RN, is Nursing Supervisor of the Operating Room. Acknowledgment: The authors thank the postanesthesia care unit nurses and OR nurses for their assistance with the data collection for this study. This research was funded by the Science and Technology Foundation Project of Shanghai Jiao Tong University School of Medicine (Jyh2204, Shanghai Nursing Association fund project 2020MS-B02). The authors have disclosed no other financial relationships related to this article. Submitted September 14, 2022; accepted in revised form October 21, 2022.
Objective:
To determine the key factors influencing intraoperative-acquired pressure injury (IAPI).
Methods:
Researchers assessed 413 surgical patients in a Shanghai tertiary hospital using an information collection form and an IAPI occurrence record form. Analysis took place using the classification and regression tree algorithm and multiple logistic regression.
Results:
A total of 43 surgical patients (10.4%) had IAPI, including 32 stage 1 cases (74.4%), and 11 stage 2 cases (25.6%). The multiple logistic regression analysis indicated that operation duration, surgical position, preoperative hypertension, and preoperative Braden Scale risk score were independently associated with IAPI development. The decision tree showed that preoperative Braden Scale score, surgical position, operation grade, operation duration, age, prealbumin level, and body mass index were important factors and that preoperative Braden Scale score was the most critical decision variable. The cross-validation method was used to indicate a model accuracy of 91.8%.
Conclusions:
The decision tree effectively identified key factors for IAPI, complementing the logistic regression analysis and providing a scientific basis for the further development of structural risk assessment, prevention, and treatment strategies for IAPI.
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