Multimodal biomarker panel for early prediction of anastomotic leak after colorectal surgery: from inflammation to ischemia

Anastomotic leakage is one of the most serious complications following colorectal surgery, with an incidence ranging from 2% to 19%, and is closely associated with increased perioperative mortality, prolonged hospital stay, and poor oncological outcomes. Traditional clinical diagnosis relies on signs, symptoms, and imaging studies, which exhibit significant time delays. In recent years, researchers have explored early warning biomarkers from multiple perspectives including inflammatory response, tissue ischemia, microbial changes, and extracellular matrix remodeling, accumulating abundant research data. This article systematically reviews the current application status of serum inflammatory markers, peritoneal drain fluid cytokines, ischemic metabolites, microbiome markers, and tissue repair-related molecules in predicting anastomotic leakage, with emphasis on analyzing the diagnostic performance, optimal detection time windows, and clinical operability of various biomarker categories. Based on this foundation, we propose a multimodal prediction framework integrating four dimensions of "inflammation-ischemia-microbiome-tissue repair" and discuss the challenges in translating this framework into clinical decision-making tools. Machine learning algorithms demonstrate application potential in integrating multi-source heterogeneous data, but insufficient external validation remains the primary bottleneck constraining clinical implementation. Future research directions should focus on large-scale multicenter prospective cohort validation, establishment of standardized detection protocols, and development of implantable real-time monitoring technologies.