Over the last decade, simulation has become a principal training method in microsurgery. With an increasing move toward the use of nonliving models, there is a need to develop methods for assessment of microvascular anastomosis skill acquisition substituting traditional patency rate. The authors present and validate a novel method of microvascular anastomosis assessment tool for formative and summative skills competency assessment.

In this study, 29 trainees with varying levels of experience in microsurgery undertook a 5-day microsurgery course. Two consecutive end-to-end microvascular anastomoses of cryopreserved rat aortas performed on day 3 and day 5 of the course were longitudinally split and photographed for randomized blinded qualitative evalua-tion. Four consecutive anastomoses by two experienced microsurgeons were analyzed as expert controls. Errors potentially leading to anastomotic leak or thrombosis were identified and logged. Statistical analysis using the Kruskal–Wallis analysis of variance (ANOVA) and a two-way repeated measure ANOVA was used to measure construct and concurrent validity, respectively.

A total of 128 microvascular anastomoses were analyzed for both student and control groups. Ten errors were identified and indexed. There was a statistically significant difference detected between average errors per anastomosis performed between groups (p < 0.05). Average errors per anastomosis was statistically decreased on day 5 of the course compared with day 3 (p < 0.001).

Evaluation of anastomosis structural patency and quality in nonliving models is possible. The proposed error list showed construct and predictive validity. The anastomosis lapse index can serve as a formative and summative assessment tool during microvascular training.

• Good: low-fi, can differentiate expert/novice
• Bad: manual ? inter-rater?; how does it correlate with real micro skills?
  • need an expert to do it

• Outcome only
• Assessor score. Bias, rating, score - statistical considerations
• Weighting - each error given equal weight – is that really the case? see Altman page 14 on Scores.
  • Experts: also made errors (between 2-2.5 errors); do they make different errors?
• Size of rat aorta?
• Can differentiate expert, but how does it correlate with patency?

• 29 participants with 2 anastomosis each on day 3 and day 5; 2 experts with 3 anastomosis on D1 and 3 on D3
  • “expert” group very concentrated
• SD for expert group higher (2.5) vs (1.0-1.3) for other groups –> there is some variability anastomosis to anastomosis

The authors quote Kaufman (whom I assume takes from Fitts-Posner), the cognitive, associative and autonomous stages in the development of technical skill (or expertise). I am not so convinced this model is entirely useful for surgical training. It is useful for some surgical task training, but not for surgery in general. See page on expertise.

• Authors suggest: ALI > 6 == novice, ALI 3-6 == intermediate, ALI < 3 == expert; BUT can you really improve so quickly as from novice to intermediate?

• See also
  • global_rating_scales
  • motion_analysis

Ghanem, A. M., Omran, Y. Al, Shatta, B., Kim, E., & Myers, S. (2016). Anastomosis Lapse Index (ALI): A Validated End Product Assessment Tool for Simulation Microsurgery Training. J Reconstr Microsurg, 32, 233–241. https://doi.org/10.1055/s-0035-1568157