Artificial Intelligence-assisted Risk Stratification in Aesthetic Surgery: A Prospective Observational Study

Area of Science:

• Medical Informatics
• Surgical Outcomes Research
• Artificial Intelligence in Medicine

Background:

• Patient safety and complication minimization are paramount in aesthetic surgery.
• An artificial intelligence (AI)-assisted risk stratification model was developed in 2021 to predict complications.
• The model aims to support clinical decision-making in aesthetic procedures.

Purpose of the Study:

• To evaluate the clinical impact of AI-assisted surgical risk stratification on patient outcomes.
• To assess the effectiveness of tailored recommendations based on risk stratification.
• To identify key risk factors influencing complications in aesthetic surgery.

Main Methods:

• A prospective observational study involving 3347 patients from January 2021 to May 2024.
• Utilized an AI model for risk stratification into high-, moderate-, and low-risk groups.
• Analyzed outcomes of 74 patients who underwent surgery, employing logistic regression and correlation tests.

Main Results:

• Of 3347 patients, 18.55% were high-risk, 30.56% moderate-risk, and 50.88% low-risk.
• Seven of 74 surgical patients (9.46%) experienced 11 complications; high-risk patients had a relative risk of 6.73.
• Age and Caprini score were independent risk factors; BMI and smoking were not significant, potentially due to AI-driven risk mitigation.

Conclusions:

• AI-assisted risk stratification effectively identifies and mitigates complications in aesthetic surgery.
• Personalized preoperative recommendations enhance patient safety and surgical outcomes.
• Integrating AI into surgical planning optimizes patient selection and clinical decision-making.