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AI Risk Assessment Model for Complication Prevention in Plastic Surgery (Artificial Intelligence)

NCT06507384 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 3347

Last updated 2024-07-18

No results posted yet for this study

Summary

The goal of this observational study is to determine if an AI-based risk assessment model can help prevent complications in plastic surgery patients by improving decision-making, providing recommendations to address risk factors, and assisting doctors in choosing the optimal timing and setting for elective plastic surgery. The study aims to answer if the AI model can effectively identify high-risk patients and what specific risk factors predict complications.

Purpose:

Evaluate the clinical effectiveness of an AI-based risk assessment model in preventing complications in plastic surgery patients by analyzing clinical data and patient history, providing personalized recommendations to mitigate risk factors and enhance outcomes.

Hypothesis:

The AI model can more accurately identify high-risk patients and provide effective recommendations to reduce complications compared to traditional methods.

Participants:

Individuals undergoing elective plastic surgery. They will complete an online form collecting data on age, height, weight, smoking habits, and comorbidities. The system calculates risk scores, BMI, and Caprini scores.

Study Procedures:

Risk assessment using the AI model, which evaluates multiple factors and generates personalized recommendations, including weight management, smoking cessation, blood pressure control, Doppler ultrasound for DVT, nutritional consultations, and specialist referrals. Recommendations are reviewed and approved by plastic surgeons.

Follow-Up:

The follow-up period ranges from 2 to 41 months, with a mean of 15 months. Data on patient outcomes, including complication rates and satisfaction, will be collected and analyzed.

Outcomes Measured:

Incidence of complications, the accuracy of the AI model in predicting complications, and its impact on improving surgical outcomes.

Impact:

The study aims to provide insights into AI use in plastic surgery, leading to better risk assessment tools and protocols, enhancing preoperative planning, postoperative care, and patient safety and satisfaction.

Conditions

  • Risk Assessment
  • Risk Factors

Interventions

OTHER

AI-Based Risk Assessment Model

Bukret AI Risk Assessment Model is a sophisticated decision support system that evaluates clinical data and patient history to generate personalized risk scores and classify patients into risk group categories for those undergoing plastic surgery. This AI model analyzes various risk factors, including BMI, age, smoking habits, and medical history, to identify potential complications. Based on the AI-generated risk group and specific risk factors, the model provides tailored recommendations for preoperative management, such as weight management, smoking cessation, blood pressure monitoring, and specialist consultations, to minimize surgical risks and improve outcomes. This intervention aims to enhance surgical planning and patient safety by offering personalized, actionable recommendations.

Sponsors & Collaborators

  • Bukret Plastic Surgery

    lead OTHER

Principal Investigators

  • Williams E Bukret, MD, EMBA

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2021-01-01
Primary Completion
2024-05-31
Completion
2024-05-31

Countries

  • Argentina

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06507384 on ClinicalTrials.gov