Microbial Spectrum and Antibiotic Sensitivity Study of Postoperative Infections in Traumatology: Discussion on Optimizing Usage Strategies

Abstract

Objective: With the increasing volume of trauma surgery, postoperative infections have garnered significant attention, as they not only affect patient outcomes but also raise healthcare costs and the risk of bacterial resistance. This study aims to analyze the microbial spectrum and antibiotic sensitivity of patients with postoperative infections in trauma surgery, providing a basis for clinical treatment and optimizing antibiotic usage strategies in this context. Methods: A retrospective analysis was conducted on patients with traumatic infections who were hospitalized in the departments of spine surgery, upper limb surgery, and lower limb surgery from January 2022 to December 2024. Bacterial culture-positive specimens were analyzed for bacterial species and antibiotic sensitivity. Results: A total of 804 traumatic infection specimens were submitted for testing, including 538 male patients (ages 2 - 95 years) and 266 female patients (ages 4 - 94 years). Among these, 267 cases showed positive culture results, with 172 males (ages 2 - 93 years) and 95 females (ages 4 - 94 years). A total of 153 strains of Gram-negative (G−) bacteria and 114 strains of Gram-positive (G+) bacteria were identified. Among G− bacteria, Escherichia coli was the most frequently isolated (40 strains), followed by Pseudomonas aeruginosa (28 strains) and Enterobacter cloacae (28 strains). Among G+ bacteria, Staphylococcus aureus was the most prevalent (75 strains), followed by Enterococcus faecalis (15 strains) and Streptococcus pyogenes (8 strains). Antibiotic sensitivity testing revealed that the resistance rate of Staphylococcus aureus to penicillin was as high as 93.33%, while the resistance rate of Escherichia coli to trimethoprim-sulfamethoxazole was 57.5%. Conclusion: The main pathogens responsible for postoperative infections in traumatology are Escherichia coli and Staphylococcus aureus, with significant antibiotic resistance. In clinical treatment, antibiotics should be selected rationally based on bacterial spectrum and resistance patterns to improve treatment efficacy.