Table 1 Consensus statements voting results.
Statement | First Round | Second Round | Final Result |
|---|---|---|---|
1. Artificial Intelligence (AI) may enable a more objective and detailed assessment of surgical skills in bariatric surgery, facilitating personalized feedback and enhancing the learning curve of surgeons in training. | 98.5% Agree | – | CONSENSUS (AGREE) |
2. Implementing AI-based systems for evaluating bariatric procedures may improve the quality of training, optimize faculty time, and increase the educational capacity of institutions. | 98.5% Agree | – | CONSENSUS (AGREE) |
3. AI can simplify bariatric surgical education. | 82.1% Agree | – | CONSENSUS (AGREE) |
4. The use of AI may help streamline operative steps in both sleeve gastrectomy and gastric bypass. | 83.8% Agree | – | CONSENSUS (AGREE) |
5. AI has a substantial contribution to patients’ education. | 85.3% Agree | – | CONSENSUS (AGREE) |
6. Patients may not fully understand the role of AI in their treatment plans. Ensuring that patients are adequately informed about how AI is used in their care and how it affects their treatment decisions is crucial for ethical practice. | 92.6% Agree | CONSENSUS (AGREE) | |
7. AI can help identify patients who qualify for bariatric surgery in a primary care setting to streamline the referral process. | 82.3% Agree | – | CONSENSUS (AGREE) |
8. AI can help in standardizing surgical procedures. | 80.9% Agree | – | CONSENSUS (AGREE) |
9. AI can be used for patient selection. | 83.8% Agree | – | CONSENSUS (AGREE) |
10. Al may develop the capability to match the appropriate operation type for patients seeking bariatric surgery. Still, the surgeon should make the final decision, especially based on the intraoperative findings. | 61.2% Agree | 91.0% Agree | CONSENSUS (AGREE) |
11. When AI systems make recommendations or decisions, it can be unclear who is accountable or responsible for those decisions, especially if outcomes are negative. | 80.9% Agree | – | CONSENSUS (AGREE) |
12. There is a potential risk that healthcare providers may over-rely on AI recommendations, which could lead to a decline in clinical skills and critical thinking. | 92.5% Agree | – | CONSENSUS (AGREE) |
13. AI and large language models (LLMS) can be used to answer clinical questions related to the field of MBS at the level of practicing surgeons. | 77.9% Agree | – | CONSENSUS (AGREE) |
14. The use of AI has the potential to identify which patients may need a diagnostic laparoscopy with negative imaging to rule out an internal hernia, but it can’t make the final decision. | 49.2% Agree | 85.1% Agree | CONSENSUS (AGREE) |
15. The integration of AI with Electronic Health Records (EHR) systems can identify patterns in social determinants of health that influence bariatric surgery outcomes, enabling more targeted pre- and post-operative support systems for underserved populations. | 88.2% Agree | – | CONSENSUS (AGREE) |
16. AI has the potential to reduce healthcare costs associated with metabolic and bariatric surgery (MBS) by optimizing surgical processes and improving patient outcomes. | 88.2% Agree | – | CONSENSUS (AGREE) |
17. AI simulation models can play an important role in evaluating diet adherence MBS. | 88.1% Agree | – | CONSENSUS (AGREE) |
18. AI can help to predict weight loss outcomes after MBS. | 83.8% Agree | – | CONSENSUS (AGREE) |
19. AI can help to predict post-MBS complications and readmission. | 75.8% Agree | – | CONSENSUS (AGREE) |
20. AI can help predict remission/relapse of obesity-associated medical problems after MBS. | 85.3% Agree | – | CONSENSUS (AGREE) |
21. Machine learning models can predict postoperative outcomes based on preoperative data, allowing for better risk stratification and tailored patient management. | 88.2% Agree | CONSENSUS (AGREE) | |
22. AI-powered wearable devices to help postoperative monitoring to facilitate early discharge(day-case) of patients. | 82.3% Agree | – | CONSENSUS (AGREE) |
23. The use of AI should comply with ethical guidelines and the General Data Protection Regulation (GDPR). | 97% Agree | – | CONSENSUS (AGREE) |
24. The use of AI in decision-making should be part of the consent process with the patient. | 88.2% Agree | – | CONSENSUS (AGREE) |
25. The introduction of AI may alter the traditional dynamics of the doctor- patient relationship, potentially affecting trust and communication. | 77.9% Agree | – | CONSENSUS (AGREE) |
26. AI learning should be a mandatory part of the surgical curriculum in the future. | 70.6% Agree | – | CONSENSUS (AGREE) |
27. Advancements in AI-driven robotics are expected to lead to more sophisticated surgical systems capable of performing complex procedures under the expert guidance of skilled surgeons. | 66.2% Agree | 91.0% Agree | CONSENSUS (AGREE) |
28. Future AI applications may include integration with genomic data to tailor interventions based on genetic predispositions to obesity and metabolic disorders. | 89.7% Agree | CONSENSUS (AGREE) |
