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

Abstract

Background

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

Abbreviations

ePOPS, early Postoperative bacterial Pneumonia and Sepsis; LASSO, Least Absolute Shrinkage and Selection Operator; ROC, the Receiver Operating characteristic Curve; AUC, the Area Under the receiver operating characteristic Curve; POD, Postoperative Day; DICS, Diagnosis of Infection after Cardiovascular Surgery; NYHA, the New York Heart Association; IL-6, InterLeukin-6; CPB, Cardiopulmonary Bypass; WBC, White Blood Cells; PCT, Procalcitonin; CRP, C-Reactive Protein; TRIPOD, the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement; CEFA, Cyclic Enhanced Fluorescent immunoassay; GOF, the Hosmer–Lemeshow goodness-of-fit test; IQR, Interquartile Range; OR, Odds Ratio; CI, Confidence Interval; IRAO, Infection-Related Adverse Outcome.

Data Sharing Statement

Readers could access the original data (http://www.medresman.org.cn/pub/cn/proj/projectshshow.aspx?proj=4148).

Ethics Approval and Consent to Participate

Ethical approval was obtained from Medical Ethics Committee of Affiliated Nanjing Drum Tower Hospital, Nanjing University Medical College, in accordance with the principles of the Declaration of Helsinki on September 23, 2020 (2020-249-01). All included patients were required to provide written informed consent.

Consent for Publication

All the authors approved the publication of the manuscript.

Acknowledgments

The trial was registered at Chinese Clinical Trial Register (www.chictr.org.cn, ChiCTR2000038762, Registered September 30, 2020).

Author Contributions

All authors contributed to data analysis, drafting or revising the article, have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

1. The Cardiovascular Disease Rescue Life Circle Project in Ili River Valley (Phase I): The No. 52 (2021) document issued by counterpart office of Jiangsu province. 2. The Clinical Medical Center of Nanjing Cardiovascular Diseases (CZLB506-2020).