Prediction model of incision infection in patients undergoing open surgery
10.3760/cma.j.cn115682-20210310-01052
- VernacularTitle:开腹手术患者切口感染预测模型的建立
- Author:
Min LIAO
1
;
Hui WU
Author Information
1. 重庆市巴南区人民医院手术室 401320
- Keywords:
Infection;
Incision;
Open surgery;
Risk factors;
Prediction model
- From:
Chinese Journal of Modern Nursing
2021;27(22):3012-3017
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish a predictive model of incision infection in patients undergoing open surgery, in order to reduce the incision infection rate of patients and improve the prognosis.Methods:The data of 248 patients who underwent open surgery in Chongqing Banan District People's Hospital from January 2018 to June 2020 were analyzed retrospectively by convenience sampling method. All patients were divided into infection group and control group, according to whether incision infection occured, with 124 cases in each group.The risk factors of incision infection in patients undergoing open surgery were analyzed by single factor and Logistic regression. The predictive value of risk factors for incision infection in patients undergoing open surgery were analyzed by ROC curve.Results:There were statistically significant differences in age, body mass index (BMI) , hypertension, type 2 diabetes, hypoproteinemia, emergency operation, skin preparation time, anesthesia method, incision type, incision length, blood pH, operative time and length of stay between the two groups of patients ( P<0.05) . The result of Logistic regression showed that the risk factors for incision infection in patients undergoing open surgery were age equal or over 60 years old, BMI equal or over 28 kg/m 2, type 2 diabetes, skin preparation time less than 10 minutes, general anesthesia, incision length equal or over 12 cm, operation time equal or over 2 hours ( P<0.05) . ROC analysis showed that age, BMI, type 2 diabetes, skin preparation time, general anesthesia, incision length and operation time had certain predictive value for incision infection in patients undergoing open surgery. The predictive value of combined application on incision infection in patients with open surgery was higher than that of single application. The area under the ROC curve was 0.887 (95% CI: 0.804 to 0.979) . Conclusions:Age equal or over 60 years old, BMI equal or over 28 kg/m 2, type 2 diabetes, skin preparation time less than 10 minutes, general anesthesia, incision length equal or over 12 cm, operation time equal or over 2 hours are the risk factors for incision infection in patients undergoing open surgery. The combined prediction model of the above factors has better predictive value for the occurrence of incision infection in patients undergoing open surgery.
