%0 Journal Article
%T Breaking Boundaries in Spinal Surgery: GPT-4's Quest to Revolutionize Surgical site Infection Management.
%A Zhao B
%A Liu H
%A Liu Q
%A Qi W
%A Zhang W
%A Du J
%A Jin Y
%A Weng X
%J J Infect Dis
%V 0
%N 0
%D 2024 Aug 13
%M 39136574
%F 7.759
%R 10.1093/infdis/jiae403
%X <B>BACKGROUND: </B>Surgical site infection (SSI) is a common and costly complication in spinal surgery. Identifying risk factors and preventive strategies is crucial for reducing SSIs. GPT-4 has evolved from a simple text-based tool to a sophisticated multimodal data expert, invaluable for clinicians. This study explored GPT-4's applications in SSI management across various clinical scenarios.<BR><B>METHODS: </B>GPT-4 was employed in various clinical scenarios related to SSIs in spinal surgery. Researchers designed specific questions for GPT-4 to generate tailored responses. Six evaluators assessed these responses for logic and accuracy using a 5-point Likert scale. Inter-rater consistency was measured with Fleiss' kappa, and radar charts visualized GPT-4's performance.<BR><B>RESULTS: </B>The inter-rater consistency, measured by Fleiss' kappa, ranged from 0.62 to 0.83. The overall average scores for logic and accuracy were 24.27±0.4 and 24.46±0.25 on 5-point Likert scale. Radar charts showed GPT-4's consistently high performance across various criteria. GPT-4 demonstrated high proficiency in creating personalized treatment plans tailored to diverse clinical patient records and offered interactive patient education. It significantly improved SSI management strategies, infection prediction models, and identified emerging research trends. However, it had limitations in fine-tuning antibiotic treatments and customizing patient education materials.<BR><B>CONCLUSIONS: </B>GPT-4 represents a significant advancement in managing SSIs in spinal surgery, promoting patient-centered care and precision medicine. Despite some limitations in antibiotic customization and patient education, GPT-4's continuous learning, attention to data privacy and security, collaboration with healthcare professionals, and patient acceptance of AI recommendations suggest its potential to revolutionize SSI management, requiring further development and clinical integration.