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Peer-reviewed veterinary case report

Postoperative complications of coronary artery bypass grafting: a narrative review on pathophysiology, management strategies, and the emerging role of artificial intelligence.

Year:
2026
Authors:
Kumar R et al.
Affiliation:
Royal College of Surgeons in Ireland

Abstract

<h4>Background and objective</h4>Coronary artery bypass grafting (CABG) remains a vital treatment option for high-risk patients with advanced coronary artery disease, especially those with multivessel disease, extensive left main disease, or refractory angina. While CABG effectively lowers long-term mortality and morbidity, it is still associated with many postoperative complications that can hinder recovery and affect quality of life. This review aims to thoroughly explore risk factors, prevention, and management strategies of major postoperative complications after CABG, categorized by physiological systems.<h4>Methods</h4>A comprehensive literature review was conducted on PubMed and Google Scholar from January 1, 2005, to August 6, 2025, without applying filters, but only including English-language publications, to gather a wide range of studies. Full texts were chosen based on set criteria, followed by a qualitative analysis to identify common themes, results, and gaps.<h4>Key content and findings</h4>Post-CABG complications span neurological, cardiac, pulmonary, renal, gastrointestinal/hepatobiliary, infectious, endocrine, and psychosocial domains. Across systems, consistently identified significant risk factors include advanced age, diabetes, renal dysfunction, prolonged cardiopulmonary bypass time, prior stroke, chronic obstructive pulmonary disease (COPD), and impaired left ventricular (LV) function. Effective preventive strategies included optimized glycemic control, early mobilization and rehabilitation, targeted use of anti-inflammatory and antioxidant therapies, prophylactic amiodarone or magnesium for atrial fibrillation (AF), strict infection-control measures, renal-protective protocols, and multimodal pain management. Recently, artificial intelligence (AI)-based tools, including machine learning models for predicting acute kidney injury, delirium, stroke, arrhythmias, and surgical-site infections, are emerging as promising adjuncts for earlier risk identification and personalized postoperative care.<h4>Conclusions</h4>Post-CABG complications remain across organ systems, emphasizing the need for early risk identification and targeted prevention. Major risk factors include age, diabetes, renal dysfunction, and prolonged bypass time. Multidisciplinary care and emerging AI-based prediction tools may improve individualized risk assessment and postoperative outcomes.

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Original publication: https://europepmc.org/article/MED/41815566