Risk factors and prediction model of postoperative atrial fibrillation surgery after esophageal cancer surgery
10.3760/cma.j.cn112434-20220805-00262
- VernacularTitle:食管癌术后新发房颤风险预测模型的构建与评价
- Author:
Qianwei WANG
1
;
Derong TANG
;
Yunyun CHEN
;
Zhenzhong ZHANG
;
Jianqiang ZHAO
Author Information
1. 南京医科大学附属淮安第一医院心胸外科，淮安 223300
- Keywords:
Esophageal cancer;
Postoperative atrial fibrillation;
Predictive models
- From:
Chinese Journal of Thoracic and Cardiovascular Surgery
2023;39(2):101-106
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To develop a risk prediction lineogram of neooperative atrial fibrillation in patients with esophageal cancer.Methods:The clinical data of 1 509 patients undergoing esophageal cancer surgery admitted to the department of esophageal surgery of our hospital from December 2019 to April 2022 were gathered, and they were divided into two layers according to whether they had new atrial fibrillation after surgery. In each layer, they were randomly divided into training set and test set in a ratio of 7∶3. In the training population, the multi-factor logistic regression method was used to establish the prediction model, and the line graph of the prediction model was drawn. The ROC curve and calibration curve were drawn to assess the differentiation ability and calibration ability of the prediction model. The test set population is used to validate the prediction model. Results:A total of 1 509 patients with esophageal cancer were included in the study, and the incidence of new atrial fibrillation after surgery was 247 patients(16.4%). A total of 1 039 patients(68.9%) were enrolled in the training set. The multivariate logistic regression model indicated that age, gender, BMI, pulmonary infection, the use of invasive ventilator, and the need for additional drainage of fluid accumulation were the influencing factors for new postoperative atrial fibrillation. The AUC of the training set prediction model under ROC curve was 0.775(95% CI: 0.737-0.812, P<0.001), indicating that the model has high predictive discrimination ability. Calibration curve and Hosmer- Lemeshow test results P=0.796, indicating that the model has good consistency of prediction ability. There were 470 subjects(31.1%) in the test set. The results showed that the AUC of the prediction model under the ROC curve was 0.773(95% CI: 0.719-0.826, P<0.001), indicating that the prediction model still has a high discriminative ability in the test set population. Conclusion:Patients with age, gender, BMI, pulmonary infection, the use of invasive ventilator, and the need for additional drainage of effusion are at higher risk of new atrial fibrillation after surgery. The timely prediction, prevention and management of POAF are crucial to improve the prognostic quality of postoperative patients with esophageal cancer by constructing clinical prediction models.
