Diagnosis of Early Bacterial Pneumonia and Sepsis After Cardiovascular Surgery: A Diagnostic Prediction Model Based on LASSO Logistic Regression

Hai-Tao Zhang,1 Kuo Wang,2 Ze-Shi Li,1 Chuang-Shi Wang,3 Xi-Kun Han,4,5 Wei Chen,6 Fu-Dong Fan,7 Jun Pan,7 Qing Zhou,7 Hai-Long Cao,7 Hao-Dong Pan,8 Xiateke Hafu,9 Chen Li,10 Guo-Liang Fan,10 Tuo Pan,1 Dong-Jin Wang,1,2,6,7 Wei Wang9 1Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Graduate School of Peking Union Medical College, Nanjing, Jiangsu, 210008, People’s Republic of China; 2Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, the Affiliated Clinical College of Xuzhou Medical University, Nanjing, Jiangsu, 210008, People’s Republic of China; 3Medical Research and Biometrics Center, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 102300, People’s Republic of China; 4Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA; 5Program in Genetic Epidemiology and Statistical Genetics, Harvard T. H. Chan School of Public Health, Boston, MA, USA; 6Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Nanjing Medical University, Nanjing, Jiangsu, 210008, People’s Republic of China; 7Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, 210008, People’s Republic of China; 8Department of Clinical Medicine, Norman Bethune Health Science Center of Jilin university, Changchun, Jilin, 130021, People’s Republic of China; 9The Xinhua Hospital of Ili Kazak Autonomous Prefecture, Ili, Xinjiang, People’s Republic of China; 10Department of Cardiac Surgery, Dong Fang Hospital Affiliated to Tongji University, Shanghai, 200120, People’s Republic of ChinaCorrespondence: Dong-Jin Wang, Chief of department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Number 321 Zhongshan Road, Nanjing, Jiangsu, 210008, People’s Republic of China, Email dongjin_wang@126.com Wei Wang, The Xinhua Hospital of Ili Kazak Autonomous Prefecture, Ili, Xinjiang, People’s Republic of China, Email wangwei3342@163.comBackground: Early postoperative bacterial pneumonia and sepsis (ePOPS), which occurs within the first 48 hours after cardiovascular surgery, is a serious life-threatening complication. Diagnosis of ePOPS is extremely challenging, and the existing diagnostic tools are insufficient. The purpose of this study was to construct a novel diagnostic prediction model for ePOPS.Methods: Least Absolute Shrinkage and Selection Operator (LASSO) with logistic regression was used to construct a model to diagnose ePOPS based on patients’ comorbidities, medical history, and laboratory findings. The area under the receiver operating characteristic curve (AUC) was used to evaluate the model discrimination.Results: A total of 1203 patients were recruited and randomly split into a training and validation set in a 7:3 ratio. By early morning on the 3rd postoperative day (POD3), 103 patients had experienced 133 episodes of bacterial pneumonia or sepsis (15 patients had both). LASSO logistic regression model showed that duration of mechanical ventilation (P=0.015), NYHA class ≥ III (P=0.001), diabetes (P< 0.001), exudation on chest radiograph (P=0.011) and IL-6 on POD3 (P< 0.001) were independent risk factors. Based on these factors, we created a nomogram named DICS-I with an AUC of 0.787 in the training set and 0.739 in the validation set.Conclusion: The DICS-I model may be used to predict the risk of ePOPS after cardiovascular surgery, and is also especially suitable for predicting the risk of IRAO. The DICS-I model could help clinicians to adjust antibiotics on the POD3.Keywords: early postoperative pneumonia and sepsis, IL-6, LASSO, nomogram