Related Experiment Video
Updated: Apr 28, 2026
Author Spotlight: Enhancing Coronary Artery Revascularization
Published on: September 15, 2023
Predicting Factors Affecting Postoperative Length of Stay in Patients Undergoing Coronary Artery Bypass Graft Surgery
Alireza Jafarkhani1, Behzad Imani1, Soheila Saeedi2
1Department of Operating Room School of Paramedicine Hamadan University of Medical Sciences Hamadan Iran.
Insights
This study reviewed factors influencing post-operative length of stay (PLOS) after coronary artery bypass graft (CABG) surgery. Machine learning identified 56 factors, with 15 key predictors impacting patient recovery times.
Area of Science:
- Cardiovascular Surgery
- Health Informatics
- Medical Data Science
Background:
- Coronary artery bypass graft (CABG) surgery is a common treatment for coronary artery disease.
- CABG surgery is associated with a prolonged post-operative length of stay (PLOS).
- Identifying factors influencing PLOS is crucial for optimizing patient care and resource management.
Purpose of the Study:
- To systematically review factors affecting PLOS in CABG patients.
- To utilize machine learning methods for identifying these influential factors.
- To provide a comprehensive overview of predictors for extended hospital stays post-CABG.
Main Methods:
- A systematic literature search was conducted across major databases (PubMed, Scopus, IEEE Xplore, Web of Science) until September 25, 2023.
- Studies investigating factors affecting PLOS in CABG patients using machine learning were included.
- The review adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
Main Results:
- Out of 9715 initially identified articles, 20 studies met the inclusion criteria.
- A total of 56 factors were identified as effective in predicting PLOS for CABG patients.
- Fifteen factors, including age, gender, ejection fraction, infection, BMI, and diabetes, were consistently reported across multiple studies.
Conclusions:
- Post-operative length of stay (PLOS) in CABG patients is multifactorial.
- Influential factors span pre-operative, intra-operative, and post-operative care domains.
- Machine learning approaches can effectively identify key predictors of PLOS in complex surgical patients.
Background And Aim:
Nowadays, coronary artery bypass graft (CABG) surgery has become a common method for treating coronary artery diseases. This surgery requires a long post-operative length of stay (PLOS) in the hospital. The purpose of this study was to systematically review the factors affecting PLOS in patients undergoing CABG surgery using machine learning methods.
Method:
A comprehensive search was conducted on PubMed, Scopus, IEEE Xplore, and Web of Science, from inception until September 25, 2023. This review was performed according to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses. All studies that investigated the factors affecting PLOS using machine learning methods in patients undergoing CABG surgery were included in the study.
Result:
In total, 9715 articles were identified after the removal of the duplicates. After the systematic screening, 20 studies met the inclusion criteria. The result showed there are 56 effective factors in predicting PLOS in patients undergoing CABG surgery. Of which 15 factors: age, gender, left ventricular ejection fraction, infection, Perceived Control (PC) levels, BMI, angina class, diabetes, Logistic Euro-score, smoking, fluid balance, inotropes, low cardiac output, atrial fibrillation, and history of cerebrovascular accident are mentioned in more than one article as an affecting factors.
Conclusion:
This systematic review highlights the multifactorial nature of PLOS, showing that patients' postoperative length of stay is influenced by factors across pre-, intra-, and postoperative care.
Related Concept Videos
01:23Peripheral Artery Disease V: Postoperative Nursing Management
01:28Cardiomyopathy VII: Pre and Post Operative Nursing Management
01:22Aneurysm IV: Nursing Management