Construction of a risk prediction model for enteral nutrition feeding intolerance in patients with abdominal trauma
10.3760/cma.j.cn115682-20230608-02292
- VernacularTitle:腹部创伤患者肠内营养喂养不耐受风险预测模型的构建
- Author:
Ping CAO
1
;
Qian CHEN
;
Xijuan LI
;
Qifang XU
Author Information
1. 郑州大学第一附属医院急诊外科，郑州 450000
- Keywords:
Abdominal trauma;
Enteral nutrition;
Feeding intolerance;
Influencing factors;
Risk prediction model
- From:
Chinese Journal of Modern Nursing
2024;30(5):656-660
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the influencing factors of enteral nutrition feeding intolerance (FI) in patients with abdominal trauma and construct a risk prediction model.Methods:This was a retrospective study. General and clinical data such as Acute Physiology and Chronic Health Evaluation (APACHEⅡ), Glasgow Coma Scale (GCS), Injury Severity Score (ISS), and Acute Gastrointestinal Injury (AGI) of patients with abdominal trauma and enteral nutrition admitted to Department of Emergency Surgery of the First Affiliated Hospital of Zhengzhou University from January 2021 to January 2023 were collected by means of medical record inquiry. Patients were divided into FI group and non-FI group according to whether FI occurred within three days after receiving enteral nutrition. Multivariate Logistic regression analysis was used to explore the influencing factors of FI in patients with abdominal injury and to construct the related risk prediction model. The diagnostic value of the prediction model was evaluated by the area under the receiver operating characteristic curve.Results:A total of 101 research objects were included, including 30 patients with enteral nutrition FI and 71 patients without enteral nutrition FI. The multivariate Logistic regression results analysis showed that injury severity score, acute gastrointestinal injury grading, and hypoalbuminemia were the influencing factors of enteral nutrition FI in patients with abdominal injury ( P<0.05). A risk prediction model for enteral nutrition FI in patients with abdominal injury was constructed based on the above factors. The area under the receiver operating characteristic curve (AUC) of the predictive model was 0.856, with a sensitivity of 0.833, a specificity of 0.732, a Jordan index of 0.565, and an optimal critical value of 0.265. Conclusions:The constructed risk prediction model for enteral nutrition FI in patients with abdominal injury has good predictive performance, which can provide a reference for medical staff to predict the risk of enteral nutrition FI in patients with abdominal injury.
