AI-Based Evaluation of Polypropylene and Polyester Meshes in Lichtenstein Hernia Repair

Aims: This study aimed to evaluate the clinical outcomes of using polypropylene and polyester mesh implants in inguinal hernia repair via the Lichtenstein technique, employing artificial intelligence and machine learning tools for statistical analysis. Methods: A total of 58 patients with primary unilateral inguinal hernias were operated on using the Lichtenstein technique over a three-year period. They were divided into two groups: Group A (38 patients, mean age 58.05 years; 34 males, 4 females) received polypropylene meshes, while Group B (20 patients, mean age 50.05 years; all males) received polyester meshes. Data analysis was conducted using Python, incorporating machine learning algorithms to assess key clinical parameters including operative time, duration of hospital stay, and postoperative complications. Results: Statistical analysis using independent samples t-tests revealed no significant differences between the two groups in terms of hernia duration, operative time, length of hospital stay, or rate of postoperative complications. Conclusions: Polypropylene and polyester meshes demonstrate comparable performance in Lichtenstein hernia repair with no significant differences in surgical outcomes. Mesh selection may therefore be guided by patient-specific factors, surgeon preference, or cost considerations, rather than expected clinical superiority.