Characterizing the learning curve for laparoscopic radical hysterectomy: buddy operating as a technique for accelerating skill acquisition.

OBJECTIVE: Total laparoscopic radical hysterectomy (TLRH) requires advanced skill in laparoscopy. We evaluated various objective measurements of surgical skill representing the learning curve throughout the first 2 years of implementation of TLRH at our institution. We also describe our technique of "buddy operating," where 2 surgeons combine referrals and operate together, thereby increasing the rate of skill acquisition. METHODS: Charts were retrospectively reviewed for 45 patients undergoing TLRH and pelvic lymphadenectomy at the Hamilton Health Sciences from August 14, 2007, to August 14, 2009. A discriminant function analysis was used to describe the learning curve. χ² and t tests were used for discrete variables. RESULTS: The most predictive learning curve model divided the sample in two, with an accurate group assignment 72.1% of the time. After the first 23 procedures, operative time was significantly shorter (201.7 vs 176.6 min, P=0.02), estimated blood loss was significantly lower (355.7 vs 196.3 mL, P=0.01), the number of lymph nodes removed was significantly higher (11.5 vs 15.3, P=0.02), and hospital length of stay was significantly shorter (1.57 vs 0.14 days, P=0.002). There were nonsignificant trends toward decreasing intraoperative complications and postoperative morbidity. CONCLUSIONS: Total laparoscopic radical hysterectomy with pelvic lymphadenectomy is an important procedure in gynecologic oncology. After a fellowship training program including laparoscopy, we demonstrate the learning curve improves after only 23 cases. This is shorter than previously reported and may be due to "buddy operating," a novel technique for reducing the learning curve in infrequently performed complex procedures.

Impact of field of study, college and year on calculation of cumulative grade point average.

A consistent finding from many reviews is that undergraduate Grade Point Average (uGPA) is a key predictor of academic success in medical school. Curiously, while uGPA has established predictive validity, little is known about its reliability. For a variety of reasons, medical schools use different weighting schemas to combine years of study. Additional concerns relate to the equivalence of grades obtained from different fields of study and institutions, with little hard data to guide conclusions. At the Michael G. DeGroote School of Medicine Class of 2007 at McMaster University, every undergraduate grade of 2,138 applicants, along with field of study and post-secondary educational institution, was analyzed. Individual grades were aggregated into an overall uGPA using published algorithms from several medical school, and correlated with a non-weighted sum. Correlations of the different schemas with equal weights ranged from 0.973 to 0.990. The extent of the difference between fields of study was small, accounting for only 1.5% of the variance. However, differences among 16 Ontario universities were larger, and accounted for 9.3% of the variance. The results of this study suggest that all weighting schemas are virtually equivalent, making any formulation reasonable. Differences by field of study are small, but do not show any bias against non-science students. Differences by institution are larger, amounting to a range in average score from 78.7 to 84.6; however it is not clear whether this reflects candidate ability or institutional policy, so attempts to correct for institution may be difficult.