Construction and application evaluation of a prediction model for incision infection in colorectal cancer patients under the enhanced recovery after surgery
10.3760/cma.j.cn211501-20240229-00456
- VernacularTitle:加速康复外科模式下结直肠癌手术患者切口感染预测模型的构建与应用价值评价
- Author:
Chao SHENG
1
;
Dan WAN
;
Fang LI
;
Tingting WANG
;
Ling CHEN
;
Jiaye AN
;
Sulan LIN
Author Information
1. 新疆医科大学护理学院，乌鲁木齐 830000
- Publication Type:Journal Article
- Keywords:
Colorectal neoplasms;
Forecasting;
Enhanced recovery after surgery;
Incision infection;
Influencing factors
- From:
Chinese Journal of Practical Nursing
2024;40(36):2812-2819
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the influencing factors of incision infection in patients undergoing colorectal cancer surgery under the standards of enhanced recovery after surgery, to establish a prediction model for the risk of postoperative incision infection and to evaluate its efficacy, providing a reference for surgical site caring of colorectal cancer patients under enhanced recovery after surgery precisely.Methods:A cross-sectional survey was used, 285 patients who underwent colorectal tumor surgery in the Department of Gastrointestinal Surgery of the First Affiliated Hospital of Xinjiang Medical University and the First Department of Gastrointestinal Surgery and the Second Department of Gastrointestinal Surgery of Xinjiang Uygur Autonomous Region Cancer Hospital from July 2023 to January 2024 were prospectively selected as the study subjects by the convenience sampling method, 225 cases were used as the modeling group and 60 cases were selected as the external validation group. The preoperative data, intraoperative data and postoperative data of subjects were collected. Postoperative incision infection was taken as the outcome index. Univariate analysis and multivariate Logistic regression analysis were used to screen the independent risk factors of postoperative incision infection of patients with colorectal tumors, and drew a nomogram, Hosmer-Lemeshow test and receiver operating characteristic (ROC) curve were used to verify the model.Results:The modeling group consisted of 131 males and 94 females aged (58.42 ± 16.24) years old. There were 35 males and 25 females in the external validation group, with an age of (57.16 ± 16.28) years. Multivariate analysis showed that malnutrition ( OR=6.614, 95% CI 2.008-21.789), length of hospital stay ( OR=1.058, 95% CI 1.004-1.114), interleukin-6 ( OR=1.041, 95% CI 1.021-1.062), and lymphocyte count ( OR=0.275, 95% CI 0.093-0.813) were independent risk factors for incision infection (all P<0.05). The area under the ROC curve of the modeling group was 0.921, the 95% CI was 0.754-0.902, the optimal cut-off value was 0.461, the sensitivity was 0.782, and the specificity was 0.785, concordance index of calibration curve was 0.971. External validation results showed that area under the ROC curve was 0.828, the 95% CI was 0.754-0.902, the optimal cut-off value was 0.438, the sensitivity was 0.745 and the specificity was 0.783. Conclusions:Under the enhanced recovery after surgery, the risk prediction model established in this study has good effect in predicting postoperative incision infection, which can provide a reference for early identification of high-risk patients with postoperative incision infection after colorectal cancer surgery.
