Maintenance training for laparoscopic suturing: the quest for the perfect timing and training model: a randomized trial

Although excellent training programs exist for acquiring the challenging skill required in laparoscopic suturing, without subsequent reinforcement, performance is prone to decay. Therefore, maintenance training is proposed to ensure better skill retention. This study aimed to elucidate the ideal timing and frequency of maintenance training as well as the best model to be used for this training. After completing a proficiency-based laparoscopic suturing training, 39 medical students attended different maintenance programs represented by four groups: a control group without additional training (group 1), a massed training group with one supervised training session (150 min) after 2.5 months (group 2), and two distributed training groups with five monthly unsupervised training sessions of 30 min on a box trainer (group 3) or the LapMentor(A (R)) (group 4). Retention testing, after 5 months, included suturing on a box trainer and on a cadaver porcine Nissen model. Performance scores (time and errors) were expressed in seconds. Afterward, time needed to regain proficiency was measured. On the box trainer, the median performance scores were 233 s (interquartile range [IQR] 27 s) for group 1, 180 s (IQR 55 s) for group 2, 169 s (IQR 26 s) for group 3, and 226 s (IQR 66 s) for group 4 (p = 0.03). No difference was seen between groups 2 and 3, both of which significantly outperformed groups 1 and 4. On the porcine Nissen model, no differences were detected between the groups (p = 0.53). Group 3 reached proficiency more quickly than the other groups. Maintenance training is a valuable and necessary addendum to proficiency-based training programs for laparoscopic suturing. A maintenance-training interval of 1 month with unsupervised training sessions on simple box trainers seems ideal. The LapMentor(A (R)) did not show any benefit. Performance differences between groups did not translate to a clinically relevant model, indicating that transfer of training is not perfect.