Open Access
CC BY 4.0 · Indian J Plast Surg 2025; 58(S 01): S5-S148
DOI: 10.1055/s-0045-1813606
Conference Abstracts

Smarter Surgery: AI-Assisted Preoperative Risk Assessment at a Tertiary Center in India

Classification of Study: Prospective Observational Study

Autoren

  • Anoosha Pius

    1   Bangalore Medical College and Research Institute, Bengaluru, Karnataka, India
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Correspondence: Anoosha Pius (E-mail: anushatresa43@gmail.com)

Abstract

Background Accurate preoperative risk prediction is critical to improving patient safety in aesthetic surgery. Artificial intelligence (AI) can integrate multiple clinical variables, stratify patients into risk categories, and suggest targeted interventions before surgery. This study evaluates the feasibility and outcomes of an AI-assisted risk assessment tool in an Indian tertiary care setting.

Methodology This prospective observational study was conducted at the Department of Plastic Surgery, Bangalore Medical College, between January 2024 and July 2025. A total of 312 patients seeking aesthetic surgery were evaluated preoperatively using an AI-based stratification model. Patients were categorized as low-risk (54.2%), moderate-risk (29.5%), or high-risk (16.3%). AI-generated recommendations, including weight optimization, smoking cessation, and specialist referral, were implemented before surgery. After optimization, 68 patients proceeded to surgery. Postoperative follow-up was maintained for 6 weeks to record complications and correlate them with the risk category.

Results Of the 68 surgical patients, 9 developed complications (overall rate 13.2%). Complication rates were as follows: low-risk: 3 of 37 (8.1%, RR = 1, reference); moderate-risk: 2 of 20 (10.0%, RR = 1.23); high-risk: 4 of 11 (36.4%, RR = 4.49). Common complications were wound infection (n = 4), seroma (n = 3), and delayed wound healing (n = 2). Logistic regression identified age and Caprini score as significant predictors. BMI and smoking status were not significant, likely due to effective preoperative optimization prompted by the AI tool.

Conclusion AI-assisted preoperative risk stratification is a feasible, practical adjunct in aesthetic surgery, even in high-volume public hospital settings. By identifying high-risk patients and enabling targeted interventions, it has the potential to reduce complications and improve surgical safety.

Keywords: AI risk stratification, preoperative assessment, aesthetic surgery, complication reduction, feasibility



Publikationsverlauf

Artikel online veröffentlicht:
10. November 2025

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