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Objective The aim of this study was to construct a Nomogram model for discriminating the risk of delirium in patients with cardiovascular surgery.Methods From January 2017 to June 2020, we collected 838 patients with cardiovascular surgery in Affiliated Hospital of Nantong University. Patients were randomly divided into a training set and a validation set in a 5:5 ratio. Nomogram model was established based on the Logistic regression. The discrimination and calibration were used to evaluate the prediction performance of the model.ResultsThe incidence of delirium was 48.3%. 389 cases were in the modeling group and 449 cases were in the verification group. Logistic regression analysis showed that CPB duration (OR=1.004, 95%CI: 1.001-1.008, P=0.018), Postoperative Serum Sodium(OR=1.112, 95%CI: 1.049-1.178, P＜0.001), age (OR=1.027, 95%CI: 1.006-1.048, P=0.011), postoperative MV(OR=1.019, 95%CI: 1.008-1.030, P＜0.001) were independent risk factors. The results showed that AUCROC was 0.712 and the 95%CI was 0.661-0.762. Hosmer-Lemeshow goodness of fit test showed that the predicted results of the model were in good agreement with the actual situation (χ2=6.200, P=0.625). The results of verification showed that AUCROC was 0.705 and the 95%CI was 0.657-0.752. Hosmer-Lemeshow goodness of fit test results showed that χ2=8.653 and P=0.372, indicating the prediction effect of the model is good.ConclusionsThe establishment of the model provides medical staff with accurate and objective assessment tools, so that medical staff can start to prevent postoperative delirium with a purpose and focus when the patient enters the CSICU after surgery.

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