Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery

Area of Science:

• Minimally Invasive Surgery
• Surgical Education
• Robotic Surgery

Background:

• Robot-assisted thyroidectomy is increasingly used, necessitating robust methods to assess surgeon proficiency.
• Current methods for measuring surgical skill lack a universally accepted standard.

Purpose of the Study:

• To evaluate the learning curve for robot-assisted thyroidectomy using multiple performance parameters.
• To determine the number of cases required to achieve proficiency in this surgical technique.

Main Methods:

• Analysis of 172 robot-assisted total thyroidectomies performed by a single surgeon.
• Cumulative summation analysis to track changes in operation time.
• Assessment of postoperative complication rates, specifically transient hypoparathyroidism.

Main Results:

• Significant improvement in operation time was observed after 50 cases (132.8 min vs. 166.9 min, p < 0.001).
• Surgeon competence, based on reduced hypoparathyroidism incidence (40.2% vs. 52.0%), was achieved after 75 cases.
• The choice of outcome measure significantly impacts the interpretation of the learning curve.

Conclusions:

• The learning curve for robot-assisted thyroidectomy varies depending on the proficiency metric used.
• A comprehensive assessment should integrate operative time, complication rates, and oncologic outcomes for accurate proficiency evaluation.