Abstract: Objective To explore the risk factors of prolonged mechanical ventilation (PMV) in patients after cardiac surgery, and to construct a risk prediction model. Methods A total of 471 patients were selected from July, 2020 to May, 2021 in department of cardiovascular surgery in a tertiary grade-A hospital in Wuhan, and divided into PMV group (n=357) and non-PMV group (n=114) according to the mechanical ventilation time. The risk factors of PMV were screened out, and the risk prediction model was constructed through logistic regression. Eight-one patients from June to November, 2021 were selected to verify the predictive value of the model. A nomogram was developed by R software and validated to predict the risk factors of PMV. Results Age (OR=1.035), BMI (OR=1.143), neutrophil count before surgery (OR=1.979), intraoperative use of antibiotic (OR=0.520), length of operation (OR=1.548), and duration of cardiopulmonary bypass (OR=1.291) were the independent risk factors of PMV. A prediction model was constructed by these 6 factors, which was internally verified by the modeling group. The calibration curve of the calibration chart was close to the ideal curve. The area under the ROC curve was 0.848. The sensitivity and specificity were 0.772, and 0.790. respectively. The external verification showed that the calibration curve of the calibration chart was near the ideal curve, and the area under the ROC curve was 0.822. The sensitivity and specificity were 0.766 and 0.824, respectively. Conclusion The risk prediction model for PMV in patients after cardiac surgery has good discrimination and accuracy. It can provide scientific guidance for individualized prevention of PMV.

Key words: cardiac surgery, prolonged mechanical ventilation, nomogram, nursing