J Reconstr Microsurg 2016; 32(03): 233-241
DOI: 10.1055/s-0035-1568157
Original Article
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Anastomosis Lapse Index (ALI): A Validated End Product Assessment Tool for Simulation Microsurgery Training

Ali M. Ghanem
1   Academic Plastic Surgery Group, Barts and The London School of Medicine and Dentistry, London, United Kingdom
,
Yasser Al Omran
1   Academic Plastic Surgery Group, Barts and The London School of Medicine and Dentistry, London, United Kingdom
,
Bashar Shatta
1   Academic Plastic Surgery Group, Barts and The London School of Medicine and Dentistry, London, United Kingdom
,
Eunsol Kim
1   Academic Plastic Surgery Group, Barts and The London School of Medicine and Dentistry, London, United Kingdom
,
Simon Myers
1   Academic Plastic Surgery Group, Barts and The London School of Medicine and Dentistry, London, United Kingdom
› Author Affiliations
Further Information

Publication History

31 March 2015

01 October 2015

Publication Date:
08 December 2015 (online)

Abstract

Background 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.

Methods 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 evaluation. 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.

Results 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).

Conclusion 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.

Note

This article was presented in the XII Congress of the European Federation of Societies for Microsurgery Barcelona, Spain, April 3–5, 2014.


 
  • References

  • 1 Reznick RK, MacRae H. Teaching surgical skills—changes in the wind. N Engl J Med 2006; 355 (25) 2664-2669
  • 2 Tsuda S, Scott D, Doyle J, Jones DB. Surgical skills training and simulation. Curr Probl Surg 2009; 46 (4) 271-370
  • 3 Ramachandran S, Ghanem AM, Myers SR. Assessment of microsurgery competency-where are we now?. Microsurgery 2013; 33 (5) 406-415
  • 4 Temple CL, Ross DC. A new, validated instrument to evaluate competency in microsurgery: the University of Western Ontario Microsurgical Skills Acquisition/Assessment instrument [outcomes article]. Plast Reconstr Surg 2011; 127 (1) 215-222
  • 5 Chan WY, Srinivasan JR, Ramakrishnan VV. Microsurgery training today and future. J Plast Reconstr Aesthet Surg 2010; 63 (6) 1061-1063
  • 6 Lascar I, Totir D, Cinca A , et al. Training program and learning curve in experimental microsurgery during the residency in plastic surgery. Microsurgery 2007; 27 (4) 263-267
  • 7 Leung CC, Ghanem AM, Tos P, Ionac M, Froschauer S, Myers SR. Towards a global understanding and standardisation of education and training in microsurgery. Arch Plast Surg 2013; 40 (4) 304-311
  • 8 Starkes JL, Payk I, Hodges NJ. Developing a standardized test for the assessment of suturing skill in novice microsurgeons. Microsurgery 1998; 18 (1) 19-22
  • 9 Ghanem AM, Hachach-Haram N, Leung CC, Myers SR. A systematic review of evidence for education and training interventions in microsurgery. Arch Plast Surg 2013; 40 (4) 312-319
  • 10 McDougall EM. Validation of surgical simulators. J Endourol 2007; 21 (3) 244-247
  • 11 Kleinert HE, Tsai TM. Microvascular repair in replantation. Clin Orthop Relat Res 1978; (133) 205-211
  • 12 Dorafshar AH, Bojovic B, Christy MR , et al. Total face, double jaw, and tongue transplantation: an evolutionary concept. Plast Reconstr Surg 2013; 131 (2) 241-251
  • 13 Holmes WJ, Williams A, Everitt KJ, Kay SP, Bourke G. Cross-over limb replantation: a case report. J Plast Reconstr Aesthet Surg 2013; 66 (10) 1428-1431
  • 14 Hui KC, Zhang F, Shaw WW , et al. Learning curve of microvascular venous anastomosis: a never ending struggle?. Microsurgery 2000; 20 (1) 22-24
  • 15 Singh M, Ziolkowski N, Ramachandran S, Myers SR, Ghanem AM. Development of a five-day basic microsurgery simulation training course: a cost analysis. Arch Plast Surg 2014; 41 (3) 213-217
  • 16 Usón J, Calles MC. Design of a new suture practice card for microsurgical training. Microsurgery 2002; 22 (8) 324-328
  • 17 Weber D, Moser N, Rösslein R. A synthetic model for microsurgical training: a surgical contribution to reduce the number of animal experiments. Eur J Pediatr Surg 1997; 7 (4) 204-206
  • 18 Grober ED, Hamstra SJ, Wanzel KR , et al. The educational impact of bench model fidelity on the acquisition of technical skill: the use of clinically relevant outcome measures. Ann Surg 2004; 240 (2) 374-381
  • 19 Bates BJ, Wimalawansa SM, Monson B, Rymer MC, Shapiro R, Johnson RM. A simple cost-effective method of microsurgical simulation training: the turkey wing model. J Reconstr Microsurg 2013; 29 (9) 615-618
  • 20 Sener S, Menovsky T, Maas AI. Use of bubble wrap for microsurgical training. J Reconstr Microsurg 2013; 29 (9) 635-636
  • 21 Nam SM, Shin HS, Kim YB, Park ES, Choi CY. Microsurgical training with porcine thigh infusion model. J Reconstr Microsurg 2013; 29 (5) 303-306
  • 22 Grober ED, Hamstra SJ, Wanzel KR , et al. Validation of novel and objective measures of microsurgical skill: Hand-motion analysis and stereoscopic visual acuity. Microsurgery 2003; 23 (4) 317-322
  • 23 Atkins JL, Kalu PU, Lannon DA, Green CJ, Butler PE. Training in microsurgical skills: Does course-based learning deliver?. Microsurgery 2005; 25 (6) 481-485
  • 24 Kaufman HH, Wiegand RL, Tunick RH. Teaching surgeons to operate—principles of psychomotor skills training. Acta Neurochir (Wien) 1987; 87 (1–2) 1-7
  • 25 Moulton CA, Dubrowski A, Macrae H, Graham B, Grober E, Reznick R. Teaching surgical skills: what kind of practice makes perfect?: a randomized, controlled trial. Ann Surg 2006; 244 (3) 400-409
  • 26 Ilie V, Ilie V, Ghetu N, Popescu S, Grosu O, Pieptu D. Assessment of the microsurgical skills: 30 minutes versus 2 weeks patency. Microsurgery 2007; 27 (5) 451-454