Abstract
BACKGROUND: Postoperative atrial fibrillation (POAF) is a common complication after cardiac surgery, which is associated with age and massive bleeding. However, whether thyroid hormone (TH) level can affect POAF remains controversial. AIM: To investigate the occurrence and risk factors of POAF, in particular, the preoperative TH level of patients was introduced into this study as a variable for analysis, and a column graph prediction model of POAF was constructed. METHODS: Patients who underwent valve surgery in Fujian Cardiac Medical Center from January 2019 to May 2022 were retrospectively analyzed and divided into POAF group and NO-POAF group. Baseline characteristics and relevant clinical data were collected from the two groups of patients. Independent risk factors for POAF were screened using univariate analysis and binary logistic regression analysis, and a column line graph prediction model was established based on the regression analysis results, and the diagnostic efficacy and calibration of the model were evaluated using the Receiver Operating Characteristic Curve (ROC) and calibration curve. RESULTS: A total of 2,340 patients underwent valve surgery, excluding 1,751 patients, a total of 589 patients were included, including 89 patients in POAF group and 500 patients in NO-POAF group. The total incidence of POAF was 15.1%. The results of the Logistics regression analysis showed that gender, age, leukocytes and TSH were risk factors of POAF. The area under the ROC curve of the nomogram prediction model for POAF was 0.747 (95% CI: 0.688-0.806, P < 0.001), with a sensitivity of 74.2% and specificity of 68%. Hosmer-Lemeshow test showed χ (2 )= 11.141, P = 0.194 > 0.05, the calibration curve was well fitted. CONCLUSION: The results of this study show that gender, age, leukocyte and TSH are risk factors of POAF, and the nomogram prediction model has a good prediction effect. Due to the limited sample size and included population, more studies are needed to validate this result.