GENOMIC BIOMARKERS FOR PREDICTING POSTOPERATIVE OUTCOMES IN GENERAL SURGERY: ADVANCES IN PRECISION SURGICAL CARE

Abstract

Postoperative complications remain an important challenge in general surgery, with substantial variation in recovery and clinical outcomes among patients undergoing similar procedures. Conventional risk-prediction methods rely mainly on clinical, physiological, and procedural factors but may not fully capture individual biological susceptibility. Genomic biomarkers offer a promising approach for improving personalized postoperative risk assessment. This comprehensive review evaluates the potential of genomic biomarkers for predicting postoperative outcomes and examines their role in advancing precision surgical care. Relevant literature was reviewed using PubMed, ScienceDirect, and Google Scholar. Evidence was synthesized across genomic biomarkers, postoperative outcome prediction, pharmacogenomics, precision surgical applications, multi-omics, and emerging predictive technologies. Genomic variation, gene-expression signatures, immune and inflammatory profiles, and pharmacogenomic markers demonstrate potential for identifying patients at increased risk of adverse postoperative outcomes and variable treatment responses. Multi-omic approaches provide broader characterization of surgical stress and recovery. Integration of molecular biomarkers with clinical data, artificial intelligence, and predictive analytics may further strengthen individualized risk stratification, perioperative decision-making, and postoperative monitoring. Genomic biomarkers may complement conventional surgical risk assessment and facilitate personalized perioperative management. However, prospective validation, standardized assessment, population diversity, and effective clinical integration remain essential before widespread implementation.