A Nomogram to Predict Acute Respiratory Distress Syndrome After Cardiac Surgery


  • Yan Liu, MD Department of Infectious Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, PR China
  • Man Song, MD Department of Infectious Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, PR China
  • Lixue Huang, MD Department of Pulmonary and Critical Care Medicine, Center for Respiratory Diseases, China-Japan Friendship Hospital, National Clinical Research, Center for Respiratory Diseases, PR China
  • Guangfa Zhu, MD, PhD Department of Pulmonary and Critical Care Medicine, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, PR China




Acute respiratory distress syndrome (ARDS), Acute lung injury, Cardiac surgery, Cardiopulmonary Bypass (CPB), Nomogram, Prediction model


Purpose: To establish a model to predict the risk of acute respiratory distress syndrome (ARDS) after cardiac surgery.

Methods: Data were collected on 132 ARDS patients, who received valvular or coronary artery bypass grafting surgery from January 2009 to December 2019. We developed the prediction model by multivariable logistic regression. Then, we used the coefficients for developing a nomogram that predicts ARDS occurrence. Internal validation was performed using resampling techniques to evaluate and optimize the model.

Results: All variables fit into the model, including albumin level before surgery (odds ratio [OR]: 0.96; 95% confidence interval [CI]: 0.92, 0.99; P = .01), cardiopulmonary bypass time (OR: 1.01; 95% CI: 1.00, 1.02; P = .02), APACHE II after surgery (OR: 1.21; 95% CI: 1.13, 1.29; P < .001), and history of diabetes (OR: 2.31; 95% CI: 1.88, 3.87; P < .001); these were considered to build the nomogram. The score distinguished ARDS patients from non-ARDS patients with an AUC of 0.785 (95% CI: 0.740, 0.830) and was well calibrated (Hosmer–Lemeshow P = .53).

Conclusions: Our developed model predicted ARDS in patients undergoing cardiac surgery and may serve as a tool for identifying patients at high risk for ARDS after cardiac surgery.


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How to Cite

Liu, Y., Song, M., Huang, L., & Zhu, G. (2021). A Nomogram to Predict Acute Respiratory Distress Syndrome After Cardiac Surgery. The Heart Surgery Forum, 24(3), E445-E450. https://doi.org/10.1532/hsf.3809